"Comparing training and testing accuracy to check over-fitting."

Avichandra

<?xml version="1.0" encoding="UTF-8"?><process version="8.2.000">
  <context>
    <input/>
    <output/>
    <macros/>
  </context>
  <operator activated="true" class="process" compatibility="8.2.000" expanded="true" name="Process">
    <parameter key="logverbosity" value="init"/>
    <parameter key="random_seed" value="2001"/>
    <parameter key="send_mail" value="never"/>
    <parameter key="notification_email" value=""/>
    <parameter key="process_duration_for_mail" value="30"/>
    <parameter key="encoding" value="SYSTEM"/>
    <process expanded="true">
      <operator activated="true" class="retrieve" compatibility="8.2.000" expanded="true" height="68" name="Retrieve totalfludata20180511" width="90" x="45" y="238">
        <parameter key="repository_entry" value="//Local Repository/totalfludata20180511"/>
      </operator>
      <operator activated="true" class="split_data" compatibility="8.2.000" expanded="true" height="103" name="Split Data" width="90" x="45" y="34">
        <enumeration key="partitions">
          <parameter key="ratio" value="0.8"/>
          <parameter key="ratio" value="0.2"/>
        </enumeration>
        <parameter key="sampling_type" value="automatic"/>
        <parameter key="use_local_random_seed" value="false"/>
        <parameter key="local_random_seed" value="1992"/>
      </operator>
      <operator activated="true" class="select_attributes" compatibility="8.2.000" expanded="true" height="82" name="Select Attributes" width="90" x="246" y="187">
        <parameter key="attribute_filter_type" value="subset"/>
        <parameter key="attribute" value=""/>
        <parameter key="attributes" value="year2017_18|year2016_17|year2015_16|wherereside.factor|weightlb|travel.factor|slaughter.factor|preg0nt.factor|pastmedreproductiveother.factor|pastmedreproductive.factor|pastmedre0ldisother.factor|pastmedre0ldisendstage.factor|pastmedre0ldis.factor|pastmedpcos.factor|pastmedothermed.factor|pastmedorgtransp.factor|pastmedneurodisstroke.factor|pastmedneurodisspi0lcord.factor|pastmedneurodisseizepilep.factor|pastmedneurodispnh.factor|pastmedneurodisother.factor|pastmedneurodisms.factor|pastmedneurodisintelldisab.factor|pastmedneurodiscp.factor|pastmedneurodis.factor|pastmedmetenddisthyroid.factor|pastmedmetenddisother.factor|pastmedmetenddisdiab.factor|pastmedmetenddis.factor|pastmedhivcd4.factor|pastmedhiv.factor|pastmedhepdisother.factor|pastmedhepdishepc.factor|pastmedhepdishepb.factor|pastmedhepdiscirr.factor|pastmedhepdis.factor|pastmedhemdissicklecell.factor|pastmedhemdisother.factor|pastmedhemdislymph.factor|pastmedhemdisleuk.factor|pastmedhemdis.factor|pastmedesld.factor|pastmedendomet.factor|pastmeddialysis.factor|pastmedcvdisvalvdis.factor|pastmedcvdisother.factor|pastmedcvdiscorartdis.factor|pastmedcvdiscongesthrtfail.factor|pastmedcvdiscongenhdis.factor|pastmedcvdiscardiomyop.factor|pastmedcvdis.factor|pastmedchronlundisother.factor|pastmedchronlundiscystfib.factor|pastmedchronlundiscopd.factor|pastmedchronlundisasth.factor|pastmedchronlundis.factor|pastmedcancerrad.factor|pastmedcancerchemo.factor|pastmedcancer.factor|pastmedautoimm.factor|menses.factor|medhistav.factor|largefarm.factor|heightin|gender.factor|foodprep.factor|fluvaccine_date.factor|fluvaccine.factor|flock.factor|farm.factor|exposure_swine.factor|exposure_poultry.factor|exposure_birds.factor|exposure.factor|exposeother.factor|exposehuman.factor|enrolling_site.factor|enrolldate|employed.factor|education.factor|edchrev_ab_ed.factor|cursympt_wheezing.factor|cursympt_stomachpain.factor|cursympt_sorethroat.factor|cursympt_sinuspain.factor|cursympt_shortnessbreath.factor|cursympt_shakingchills.factor|cursympt_rhinorrhea.factor|cursympt_other.factor|cursympt_incrsputum.factor|cursympt_headache.factor|cursympt_getoutofbed.factor|cursympt_fever.factor|cursympt_fatigue.factor|cursympt_diarrhea.factor|cursympt_coughsputum.factor|cursympt_cough.factor|cursympt_conjunctivitis.factor|cursympt_chestpain.factor|cursympt_chesthurt.factor|cursympt_bodyaches.factor|cursympt_appetite.factor|cursympt_0usea.factor|curmedsteroids.factor|curmedimmunosupsp___4.factor|curmedimmunosupsp___3.factor|curmedimmunosupsp___2.factor|curmedimmunosupsp___1.factor|curmedimmunosup.factor|breastfeeding.factor|bcmethod.factor|age|admit.factor|H3|H1|B"/>
        <parameter key="use_except_expression" value="false"/>
        <parameter key="value_type" value="attribute_value"/>
        <parameter key="use_value_type_exception" value="false"/>
        <parameter key="except_value_type" value="time"/>
        <parameter key="block_type" value="attribute_block"/>
        <parameter key="use_block_type_exception" value="false"/>
        <parameter key="except_block_type" value="value_matrix_row_start"/>
        <parameter key="invert_selection" value="false"/>
        <parameter key="include_special_attributes" value="false"/>
      </operator>
      <operator activated="true" class="set_role" compatibility="8.2.000" expanded="true" height="82" name="Set Role" width="90" x="179" y="34">
        <parameter key="attribute_name" value="GeneXpert"/>
        <parameter key="target_role" value="label"/>
        <list key="set_additional_roles"/>
      </operator>
      <operator activated="true" class="split_validation" compatibility="8.2.000" expanded="true" height="124" name="Validation" width="90" x="313" y="34">
        <parameter key="create_complete_model" value="false"/>
        <parameter key="split" value="relative"/>
        <parameter key="split_ratio" value="0.7"/>
        <parameter key="training_set_size" value="100"/>
        <parameter key="test_set_size" value="-1"/>
        <parameter key="sampling_type" value="automatic"/>
        <parameter key="use_local_random_seed" value="false"/>
        <parameter key="local_random_seed" value="1992"/>
        <process expanded="true">
          <operator activated="true" class="concurrency:parallel_random_forest" compatibility="8.2.000" expanded="true" height="103" name="Random Forest" width="90" x="112" y="34">
            <parameter key="number_of_trees" value="10"/>
            <parameter key="criterion" value="gain_ratio"/>
            <parameter key="maximal_depth" value="20"/>
            <parameter key="apply_pruning" value="true"/>
            <parameter key="confidence" value="0.25"/>
            <parameter key="apply_prepruning" value="true"/>
            <parameter key="minimal_gain" value="0.1"/>
            <parameter key="minimal_leaf_size" value="2"/>
            <parameter key="minimal_size_for_split" value="4"/>
            <parameter key="number_of_prepruning_alternatives" value="3"/>
            <parameter key="random_splits" value="false"/>
            <parameter key="guess_subset_ratio" value="true"/>
            <parameter key="subset_ratio" value="0.2"/>
            <parameter key="voting_strategy" value="confidence vote"/>
            <parameter key="use_local_random_seed" value="false"/>
            <parameter key="local_random_seed" value="1992"/>
            <parameter key="enable_parallel_execution" value="true"/>
          </operator>
          <connect from_port="training" to_op="Random Forest" to_port="training set"/>
          <connect from_op="Random Forest" from_port="model" to_port="model"/>
          <portSpacing port="source_training" spacing="0"/>
          <portSpacing port="sink_model" spacing="0"/>
          <portSpacing port="sink_through 1" spacing="0"/>
        </process>
        <process expanded="true">
          <operator activated="true" class="apply_model" compatibility="8.2.000" expanded="true" height="82" name="Apply Model (2)" width="90" x="45" y="34">
            <list key="application_parameters"/>
            <parameter key="create_view" value="false"/>
          </operator>
          <operator activated="true" class="performance" compatibility="8.2.000" expanded="true" height="82" name="Performance" width="90" x="179" y="34">
            <parameter key="use_example_weights" value="true"/>
          </operator>
          <connect from_port="model" to_op="Apply Model (2)" to_port="model"/>
          <connect from_port="test set" to_op="Apply Model (2)" to_port="unlabelled data"/>
          <connect from_op="Apply Model (2)" from_port="labelled data" to_op="Performance" to_port="labelled data"/>
          <connect from_op="Performance" from_port="performance" to_port="averagable 1"/>
          <portSpacing port="source_model" spacing="0"/>
          <portSpacing port="source_test set" spacing="0"/>
          <portSpacing port="source_through 1" spacing="0"/>
          <portSpacing port="sink_averagable 1" spacing="0"/>
          <portSpacing port="sink_averagable 2" spacing="0"/>
        </process>
      </operator>
      <operator activated="true" class="apply_model" compatibility="8.2.000" expanded="true" height="82" name="Apply Model" width="90" x="447" y="136">
        <list key="application_parameters"/>
        <parameter key="create_view" value="false"/>
      </operator>
      <connect from_op="Retrieve totalfludata20180511" from_port="output" to_op="Split Data" to_port="example set"/>
      <connect from_op="Split Data" from_port="partition 1" to_op="Set Role" to_port="example set input"/>
      <connect from_op="Split Data" from_port="partition 2" to_op="Select Attributes" to_port="example set input"/>
      <connect from_op="Select Attributes" from_port="example set output" to_op="Apply Model" to_port="unlabelled data"/>
      <connect from_op="Set Role" from_port="example set output" to_op="Validation" to_port="training"/>
      <connect from_op="Validation" from_port="model" to_op="Apply Model" to_port="model"/>
      <connect from_op="Validation" from_port="averagable 1" to_port="result 1"/>
      <connect from_op="Apply Model" from_port="labelled data" to_port="result 2"/>
      <portSpacing port="source_input 1" spacing="0"/>
      <portSpacing port="sink_result 1" spacing="0"/>
      <portSpacing port="sink_result 2" spacing="0"/>
      <portSpacing port="sink_result 3" spacing="0"/>
    </process>
  </operator>
</process>

I have designed a random forest classification model with splitting the dataset into training and testing in a ratio of 0.8:0.2. I have validated the model. I got accuracy for the testing dataset. I want to check the over-fitting problem of my model. So, I want to compare accuracy for both training and testing data set. How to retrieve accuracy for both training and testing dataset from my model. 

kypexin

Hi @Avichandra

 

In your process, add second PERFORMANCE operator and connect is with lab output of APPLY MODEL, this way you'll also get performance measure for 0.2 test split data.

 

Avichandra

Thank you very much! I got what I wanted to know.

Avichandra

<?xml version="1.0" encoding="UTF-8"?><process version="8.2.000">
  <context>
    <input/>
    <output/>
    <macros/>
  </context>
  <operator activated="true" automodel="EXPORTED" class="process" compatibility="8.2.000" expanded="true" name="Process">
    <parameter key="logverbosity" value="init"/>
    <parameter key="random_seed" value="2001"/>
    <parameter key="send_mail" value="never"/>
    <parameter key="notification_email" value=""/>
    <parameter key="process_duration_for_mail" value="30"/>
    <parameter key="encoding" value="SYSTEM"/>
    <process expanded="true">
      <operator activated="true" automodel="EXPORTED" class="retrieve" compatibility="8.2.000" expanded="true" height="68" name="Retrieve Data" width="90" x="45" y="238">
        <parameter key="repository_entry" value="//Local Repository/totalfludata20180511"/>
        <description align="center" color="transparent" colored="false" width="126">Load data.</description>
      </operator>
      <operator activated="true" automodel="EXPORTED" class="subprocess" compatibility="8.2.000" expanded="true" height="82" name="Preprocessing" width="90" x="179" y="238">
        <process expanded="true">
          <operator activated="true" automodel="EXPORTED" class="select_subprocess" compatibility="8.2.000" expanded="true" height="82" name="Define Target?" width="90" x="45" y="34">
            <parameter key="select_which" value="2"/>
            <process expanded="true">
              <connect from_port="input 1" to_port="output 1"/>
              <portSpacing port="source_input 1" spacing="0"/>
              <portSpacing port="source_input 2" spacing="0"/>
              <portSpacing port="sink_output 1" spacing="0"/>
              <portSpacing port="sink_output 2" spacing="0"/>
            </process>
            <process expanded="true">
              <operator activated="true" automodel="EXPORTED" class="set_role" compatibility="8.2.000" expanded="true" height="82" name="Define Target" width="90" x="45" y="34">
                <parameter key="attribute_name" value="GeneXpert"/>
                <parameter key="target_role" value="label"/>
                <list key="set_additional_roles"/>
                <description align="center" color="transparent" colored="false" width="126">Define the target column for the predictive model.</description>
              </operator>
              <connect from_port="input 1" to_op="Define Target" to_port="example set input"/>
              <connect from_op="Define Target" from_port="example set output" to_port="output 1"/>
              <portSpacing port="source_input 1" spacing="0"/>
              <portSpacing port="source_input 2" spacing="0"/>
              <portSpacing port="sink_output 1" spacing="0"/>
              <portSpacing port="sink_output 2" spacing="0"/>
            </process>
            <description align="center" color="transparent" colored="false" width="126">Should define a target column?</description>
          </operator>
          <operator activated="true" automodel="EXPORTED" class="select_subprocess" compatibility="8.2.000" expanded="true" height="82" name="Should Discretize?" width="90" x="179" y="34">
            <parameter key="select_which" value="1"/>
            <process expanded="true">
              <connect from_port="input 1" to_port="output 1"/>
              <portSpacing port="source_input 1" spacing="0"/>
              <portSpacing port="source_input 2" spacing="0"/>
              <portSpacing port="sink_output 1" spacing="0"/>
              <portSpacing port="sink_output 2" spacing="0"/>
            </process>
            <process expanded="true">
              <operator activated="true" automodel="EXPORTED" class="discretize_by_bins" compatibility="8.2.000" expanded="true" height="103" name="Binning" width="90" x="45" y="34">
                <parameter key="return_preprocessing_model" value="false"/>
                <parameter key="create_view" value="false"/>
                <parameter key="attribute_filter_type" value="single"/>
                <parameter key="attribute" value="Age"/>
                <parameter key="attributes" value=""/>
                <parameter key="use_except_expression" value="false"/>
                <parameter key="value_type" value="numeric"/>
                <parameter key="use_value_type_exception" value="false"/>
                <parameter key="except_value_type" value="real"/>
                <parameter key="block_type" value="value_series"/>
                <parameter key="use_block_type_exception" value="false"/>
                <parameter key="except_block_type" value="value_series_end"/>
                <parameter key="invert_selection" value="false"/>
                <parameter key="include_special_attributes" value="true"/>
                <parameter key="number_of_bins" value="2"/>
                <parameter key="define_boundaries" value="false"/>
                <parameter key="range_name_type" value="short"/>
                <parameter key="automatic_number_of_digits" value="true"/>
                <parameter key="number_of_digits" value="3"/>
                <description align="center" color="transparent" colored="false" width="126">Discretize by binning (same range per bin).</description>
              </operator>
              <connect from_port="input 1" to_op="Binning" to_port="example set input"/>
              <connect from_op="Binning" from_port="example set output" to_port="output 1"/>
              <portSpacing port="source_input 1" spacing="0"/>
              <portSpacing port="source_input 2" spacing="0"/>
              <portSpacing port="sink_output 1" spacing="0"/>
              <portSpacing port="sink_output 2" spacing="0"/>
            </process>
            <process expanded="true">
              <operator activated="true" automodel="EXPORTED" class="discretize_by_frequency" compatibility="8.2.000" expanded="true" height="103" name="Frequency" width="90" x="45" y="34">
                <parameter key="return_preprocessing_model" value="false"/>
                <parameter key="create_view" value="false"/>
                <parameter key="attribute_filter_type" value="single"/>
                <parameter key="attribute" value="Age"/>
                <parameter key="attributes" value=""/>
                <parameter key="use_except_expression" value="false"/>
                <parameter key="value_type" value="numeric"/>
                <parameter key="use_value_type_exception" value="false"/>
                <parameter key="except_value_type" value="real"/>
                <parameter key="block_type" value="value_series"/>
                <parameter key="use_block_type_exception" value="false"/>
                <parameter key="except_block_type" value="value_series_end"/>
                <parameter key="invert_selection" value="false"/>
                <parameter key="include_special_attributes" value="true"/>
                <parameter key="use_sqrt_of_examples" value="false"/>
                <parameter key="number_of_bins" value="2"/>
                <parameter key="range_name_type" value="short"/>
                <parameter key="automatic_number_of_digits" value="true"/>
                <parameter key="number_of_digits" value="-1"/>
                <description align="center" color="transparent" colored="false" width="126">Discretize by frequency (same count per bin).</description>
              </operator>
              <connect from_port="input 1" to_op="Frequency" to_port="example set input"/>
              <connect from_op="Frequency" from_port="example set output" to_port="output 1"/>
              <portSpacing port="source_input 1" spacing="0"/>
              <portSpacing port="source_input 2" spacing="0"/>
              <portSpacing port="sink_output 1" spacing="0"/>
              <portSpacing port="sink_output 2" spacing="0"/>
            </process>
            <description align="center" color="transparent" colored="false" width="126">Should discretize numerical target column?</description>
          </operator>
          <operator activated="true" automodel="EXPORTED" class="select_subprocess" compatibility="8.2.000" expanded="true" height="82" name="Map Values?" width="90" x="313" y="34">
            <parameter key="select_which" value="1"/>
            <process expanded="true">
              <connect from_port="input 1" to_port="output 1"/>
              <portSpacing port="source_input 1" spacing="0"/>
              <portSpacing port="source_input 2" spacing="0"/>
              <portSpacing port="sink_output 1" spacing="0"/>
              <portSpacing port="sink_output 2" spacing="0"/>
            </process>
            <process expanded="true">
              <operator activated="true" automodel="EXPORTED" class="map" compatibility="8.2.000" expanded="true" height="82" name="Map Values" width="90" x="45" y="34">
                <parameter key="attribute_filter_type" value="single"/>
                <parameter key="attribute" value="Survived"/>
                <parameter key="attributes" value=""/>
                <parameter key="use_except_expression" value="false"/>
                <parameter key="value_type" value="attribute_value"/>
                <parameter key="use_value_type_exception" value="false"/>
                <parameter key="except_value_type" value="time"/>
                <parameter key="block_type" value="attribute_block"/>
                <parameter key="use_block_type_exception" value="false"/>
                <parameter key="except_block_type" value="value_matrix_row_start"/>
                <parameter key="invert_selection" value="false"/>
                <parameter key="include_special_attributes" value="true"/>
                <list key="value_mappings"/>
                <parameter key="consider_regular_expressions" value="false"/>
                <parameter key="add_default_mapping" value="false"/>
                <description align="center" color="transparent" colored="false" width="126">Map some nominal target values to new values.</description>
              </operator>
              <connect from_port="input 1" to_op="Map Values" to_port="example set input"/>
              <connect from_op="Map Values" from_port="example set output" to_port="output 1"/>
              <portSpacing port="source_input 1" spacing="0"/>
              <portSpacing port="source_input 2" spacing="0"/>
              <portSpacing port="sink_output 1" spacing="0"/>
              <portSpacing port="sink_output 2" spacing="0"/>
            </process>
            <description align="center" color="transparent" colored="false" width="126">Should map nominal values?</description>
          </operator>
          <operator activated="true" automodel="EXPORTED" class="select_subprocess" compatibility="8.2.000" expanded="true" height="82" name="Positive Class?" width="90" x="447" y="34">
            <parameter key="select_which" value="2"/>
            <process expanded="true">
              <connect from_port="input 1" to_port="output 1"/>
              <portSpacing port="source_input 1" spacing="0"/>
              <portSpacing port="source_input 2" spacing="0"/>
              <portSpacing port="sink_output 1" spacing="0"/>
              <portSpacing port="sink_output 2" spacing="0"/>
            </process>
            <process expanded="true">
              <operator activated="true" automodel="EXPORTED" class="nominal_to_binominal" compatibility="8.2.000" expanded="true" height="103" name="Nominal to Binominal" width="90" x="45" y="34">
                <parameter key="return_preprocessing_model" value="false"/>
                <parameter key="create_view" value="false"/>
                <parameter key="attribute_filter_type" value="single"/>
                <parameter key="attribute" value="GeneXpert"/>
                <parameter key="attributes" value=""/>
                <parameter key="use_except_expression" value="false"/>
                <parameter key="value_type" value="nominal"/>
                <parameter key="use_value_type_exception" value="false"/>
                <parameter key="except_value_type" value="file_path"/>
                <parameter key="block_type" value="single_value"/>
                <parameter key="use_block_type_exception" value="false"/>
                <parameter key="except_block_type" value="single_value"/>
                <parameter key="invert_selection" value="false"/>
                <parameter key="include_special_attributes" value="true"/>
                <parameter key="transform_binominal" value="false"/>
                <parameter key="use_underscore_in_name" value="false"/>
                <description align="center" color="transparent" colored="false" width="126">Make sure that target is binary for positive class mapping.</description>
              </operator>
              <operator activated="true" automodel="EXPORTED" class="remap_binominals" compatibility="8.2.000" expanded="true" height="82" name="Define Positive Class" width="90" x="179" y="34">
                <parameter key="attribute_filter_type" value="single"/>
                <parameter key="attribute" value="GeneXpert"/>
                <parameter key="attributes" value=""/>
                <parameter key="use_except_expression" value="false"/>
                <parameter key="value_type" value="binominal"/>
                <parameter key="use_value_type_exception" value="false"/>
                <parameter key="except_value_type" value="binominal"/>
                <parameter key="block_type" value="value_matrix_start"/>
                <parameter key="use_block_type_exception" value="false"/>
                <parameter key="except_block_type" value="value_matrix_start"/>
                <parameter key="invert_selection" value="false"/>
                <parameter key="include_special_attributes" value="true"/>
                <parameter key="negative_value" value="Negative"/>
                <parameter key="positive_value" value="Positive"/>
                <description align="center" color="transparent" colored="false" width="126">Potentially define which one should be the positive class.</description>
              </operator>
              <connect from_port="input 1" to_op="Nominal to Binominal" to_port="example set input"/>
              <connect from_op="Nominal to Binominal" from_port="example set output" to_op="Define Positive Class" to_port="example set input"/>
              <connect from_op="Define Positive Class" from_port="example set output" to_port="output 1"/>
              <portSpacing port="source_input 1" spacing="0"/>
              <portSpacing port="source_input 2" spacing="0"/>
              <portSpacing port="sink_output 1" spacing="0"/>
              <portSpacing port="sink_output 2" spacing="0"/>
            </process>
            <description align="center" color="transparent" colored="false" width="126">Should define positive class?</description>
          </operator>
          <operator activated="true" automodel="EXPORTED" class="select_subprocess" compatibility="8.2.000" expanded="true" height="82" name="Remove Columns?" width="90" x="581" y="34">
            <parameter key="select_which" value="1"/>
            <process expanded="true">
              <connect from_port="input 1" to_port="output 1"/>
              <portSpacing port="source_input 1" spacing="0"/>
              <portSpacing port="source_input 2" spacing="0"/>
              <portSpacing port="sink_output 1" spacing="0"/>
              <portSpacing port="sink_output 2" spacing="0"/>
            </process>
            <process expanded="true">
              <operator activated="true" automodel="EXPORTED" class="select_attributes" compatibility="8.2.000" expanded="true" height="82" name="Remove Columns" width="90" x="45" y="34">
                <parameter key="attribute_filter_type" value="regular_expression"/>
                <parameter key="attribute" value=""/>
                <parameter key="attributes" value=""/>
                <parameter key="regular_expression" value="Name|Ticket Number|Cabin|Life Boat"/>
                <parameter key="use_except_expression" value="false"/>
                <parameter key="value_type" value="attribute_value"/>
                <parameter key="use_value_type_exception" value="false"/>
                <parameter key="except_value_type" value="time"/>
                <parameter key="block_type" value="attribute_block"/>
                <parameter key="use_block_type_exception" value="false"/>
                <parameter key="except_block_type" value="value_matrix_row_start"/>
                <parameter key="invert_selection" value="true"/>
                <parameter key="include_special_attributes" value="true"/>
                <description align="center" color="transparent" colored="false" width="126">Potentially remove columns.</description>
              </operator>
              <connect from_port="input 1" to_op="Remove Columns" to_port="example set input"/>
              <connect from_op="Remove Columns" from_port="example set output" to_port="output 1"/>
              <portSpacing port="source_input 1" spacing="0"/>
              <portSpacing port="source_input 2" spacing="0"/>
              <portSpacing port="sink_output 1" spacing="0"/>
              <portSpacing port="sink_output 2" spacing="0"/>
            </process>
            <description align="center" color="transparent" colored="false" width="126">Should remove columns?</description>
          </operator>
          <operator activated="true" automodel="EXPORTED" class="subprocess" compatibility="8.2.000" expanded="true" height="82" name="Unify Value Types" width="90" x="715" y="34">
            <process expanded="true">
              <operator activated="true" automodel="EXPORTED" class="select_attributes" compatibility="8.2.000" expanded="true" height="82" name="Remove Dates" width="90" x="45" y="34">
                <parameter key="attribute_filter_type" value="value_type"/>
                <parameter key="attribute" value=""/>
                <parameter key="attributes" value=""/>
                <parameter key="use_except_expression" value="false"/>
                <parameter key="value_type" value="date_time"/>
                <parameter key="use_value_type_exception" value="false"/>
                <parameter key="except_value_type" value="time"/>
                <parameter key="block_type" value="attribute_block"/>
                <parameter key="use_block_type_exception" value="false"/>
                <parameter key="except_block_type" value="value_matrix_row_start"/>
                <parameter key="invert_selection" value="true"/>
                <parameter key="include_special_attributes" value="false"/>
                <description align="center" color="transparent" colored="false" width="126">Remove all date columns.</description>
              </operator>
              <operator activated="true" automodel="EXPORTED" class="nominal_to_text" compatibility="8.2.000" expanded="true" height="82" name="Nominal to Text" width="90" x="179" y="34">
                <parameter key="attribute_filter_type" value="value_type"/>
                <parameter key="attribute" value=""/>
                <parameter key="attributes" value=""/>
                <parameter key="use_except_expression" value="false"/>
                <parameter key="value_type" value="nominal"/>
                <parameter key="use_value_type_exception" value="false"/>
                <parameter key="except_value_type" value="file_path"/>
                <parameter key="block_type" value="single_value"/>
                <parameter key="use_block_type_exception" value="false"/>
                <parameter key="except_block_type" value="single_value"/>
                <parameter key="invert_selection" value="false"/>
                <parameter key="include_special_attributes" value="true"/>
                <description align="center" color="transparent" colored="false" width="126">Transform all nominal columns to text so that we make sure that all will have polynominal type after the next transformation.</description>
              </operator>
              <operator activated="true" automodel="EXPORTED" class="text_to_nominal" compatibility="8.2.000" expanded="true" height="82" name="Text to Nominal" width="90" x="313" y="34">
                <parameter key="attribute_filter_type" value="value_type"/>
                <parameter key="attribute" value=""/>
                <parameter key="attributes" value=""/>
                <parameter key="use_except_expression" value="false"/>
                <parameter key="value_type" value="text"/>
                <parameter key="use_value_type_exception" value="false"/>
                <parameter key="except_value_type" value="text"/>
                <parameter key="block_type" value="value_matrix"/>
                <parameter key="use_block_type_exception" value="false"/>
                <parameter key="except_block_type" value="value_matrix_row_start"/>
                <parameter key="invert_selection" value="false"/>
                <parameter key="include_special_attributes" value="true"/>
                <description align="center" color="transparent" colored="false" width="126">Transform all text columns into polynominal columns.</description>
              </operator>
              <operator activated="true" automodel="EXPORTED" class="numerical_to_real" compatibility="8.2.000" expanded="true" height="82" name="Numerical to Real" width="90" x="447" y="34">
                <parameter key="attribute_filter_type" value="value_type"/>
                <parameter key="attribute" value=""/>
                <parameter key="attributes" value=""/>
                <parameter key="use_except_expression" value="false"/>
                <parameter key="value_type" value="numeric"/>
                <parameter key="use_value_type_exception" value="true"/>
                <parameter key="except_value_type" value="integer"/>
                <parameter key="block_type" value="value_series"/>
                <parameter key="use_block_type_exception" value="false"/>
                <parameter key="except_block_type" value="value_series_end"/>
                <parameter key="invert_selection" value="false"/>
                <parameter key="include_special_attributes" value="true"/>
                <description align="center" color="transparent" colored="false" width="126">Turn all numerical columns (not integers though) into real columns.</description>
              </operator>
              <connect from_port="in 1" to_op="Remove Dates" to_port="example set input"/>
              <connect from_op="Remove Dates" from_port="example set output" to_op="Nominal to Text" to_port="example set input"/>
              <connect from_op="Nominal to Text" from_port="example set output" to_op="Text to Nominal" to_port="example set input"/>
              <connect from_op="Text to Nominal" from_port="example set output" to_op="Numerical to Real" to_port="example set input"/>
              <connect from_op="Numerical to Real" from_port="example set output" to_port="out 1"/>
              <portSpacing port="source_in 1" spacing="0"/>
              <portSpacing port="source_in 2" spacing="0"/>
              <portSpacing port="sink_out 1" spacing="0"/>
              <portSpacing port="sink_out 2" spacing="0"/>
            </process>
            <description align="center" color="transparent" colored="false" width="126">Unify all value types</description>
          </operator>
          <connect from_port="in 1" to_op="Define Target?" to_port="input 1"/>
          <connect from_op="Define Target?" from_port="output 1" to_op="Should Discretize?" to_port="input 1"/>
          <connect from_op="Should Discretize?" from_port="output 1" to_op="Map Values?" to_port="input 1"/>
          <connect from_op="Map Values?" from_port="output 1" to_op="Positive Class?" to_port="input 1"/>
          <connect from_op="Positive Class?" from_port="output 1" to_op="Remove Columns?" to_port="input 1"/>
          <connect from_op="Remove Columns?" from_port="output 1" to_op="Unify Value Types" to_port="in 1"/>
          <connect from_op="Unify Value Types" from_port="out 1" to_port="out 1"/>
          <portSpacing port="source_in 1" spacing="0"/>
          <portSpacing port="source_in 2" spacing="0"/>
          <portSpacing port="sink_out 1" spacing="0"/>
          <portSpacing port="sink_out 2" spacing="0"/>
        </process>
        <description align="center" color="transparent" colored="false" width="126">All general preprocessing steps happen inside this operator - double click on it to see the details.</description>
      </operator>
      <operator activated="true" automodel="EXPORTED" class="subprocess" compatibility="8.2.000" expanded="true" height="82" name="Replace Missing Values" width="90" x="313" y="238">
        <process expanded="true">
          <operator activated="true" automodel="EXPORTED" class="generate_attributes" compatibility="8.2.000" expanded="true" height="82" name="Generate Dummy" width="90" x="45" y="34">
            <list key="function_descriptions">
              <parameter key="DUMMY_NOMINAL_ATTRIBUTE_TO_DELETE" value="&quot;dummy&quot;"/>
            </list>
            <parameter key="keep_all" value="true"/>
            <description align="center" color="transparent" colored="false" width="126">Add a dummy nominal attribute to make sure that the loop will always deliver a result.</description>
          </operator>
          <operator activated="true" automodel="EXPORTED" class="concurrency:loop_attributes" compatibility="8.2.000" expanded="true" height="82" name="Loop Nominal Attributes" width="90" x="179" y="34">
            <parameter key="attribute_filter_type" value="value_type"/>
            <parameter key="attribute" value=""/>
            <parameter key="attributes" value=""/>
            <parameter key="use_except_expression" value="false"/>
            <parameter key="value_type" value="nominal"/>
            <parameter key="use_value_type_exception" value="false"/>
            <parameter key="except_value_type" value="time"/>
            <parameter key="block_type" value="attribute_block"/>
            <parameter key="use_block_type_exception" value="false"/>
            <parameter key="except_block_type" value="value_matrix_row_start"/>
            <parameter key="invert_selection" value="false"/>
            <parameter key="include_special_attributes" value="false"/>
            <parameter key="attribute_name_macro" value="nominal_attribute"/>
            <parameter key="reuse_results" value="true"/>
            <parameter key="enable_parallel_execution" value="true"/>
            <process expanded="true">
              <operator activated="true" automodel="EXPORTED" class="extract_macro" compatibility="8.2.000" expanded="true" height="68" name="Calculate No of Missings" width="90" x="45" y="34">
                <parameter key="macro" value="no_missings"/>
                <parameter key="macro_type" value="statistics"/>
                <parameter key="statistics" value="unknown"/>
                <parameter key="attribute_name" value="%{nominal_attribute}"/>
                <list key="additional_macros"/>
                <description align="center" color="transparent" colored="false" width="126">Calculate the number of missing values for this nominal attribute.</description>
              </operator>
              <operator activated="true" automodel="EXPORTED" class="branch" compatibility="8.2.000" expanded="true" height="103" name="Branch" width="90" x="179" y="34">
                <parameter key="condition_type" value="expression"/>
                <parameter key="expression" value="eval(%{no_missings})==0"/>
                <parameter key="io_object" value="ANOVAMatrix"/>
                <parameter key="return_inner_output" value="true"/>
                <process expanded="true">
                  <connect from_port="input 1" to_port="input 1"/>
                  <portSpacing port="source_condition" spacing="0"/>
                  <portSpacing port="source_input 1" spacing="0"/>
                  <portSpacing port="source_input 2" spacing="0"/>
                  <portSpacing port="sink_input 1" spacing="0"/>
                  <portSpacing port="sink_input 2" spacing="0"/>
                </process>
                <process expanded="true">
                  <operator activated="true" automodel="EXPORTED" class="replace_missing_values" compatibility="8.2.000" expanded="true" height="103" name="Replace Nominal Missings" width="90" x="112" y="34">
                    <parameter key="return_preprocessing_model" value="false"/>
                    <parameter key="create_view" value="false"/>
                    <parameter key="attribute_filter_type" value="single"/>
                    <parameter key="attribute" value="%{nominal_attribute}"/>
                    <parameter key="attributes" value=""/>
                    <parameter key="use_except_expression" value="false"/>
                    <parameter key="value_type" value="nominal"/>
                    <parameter key="use_value_type_exception" value="false"/>
                    <parameter key="except_value_type" value="time"/>
                    <parameter key="block_type" value="attribute_block"/>
                    <parameter key="use_block_type_exception" value="false"/>
                    <parameter key="except_block_type" value="value_matrix_row_start"/>
                    <parameter key="invert_selection" value="false"/>
                    <parameter key="include_special_attributes" value="false"/>
                    <parameter key="default" value="value"/>
                    <list key="columns"/>
                    <parameter key="replenishment_value" value="MISSING"/>
                    <description align="center" color="transparent" colored="false" width="126">Replace nominal missings with the word 'missing'.</description>
                  </operator>
                  <connect from_port="input 1" to_op="Replace Nominal Missings" to_port="example set input"/>
                  <connect from_op="Replace Nominal Missings" from_port="example set output" to_port="input 1"/>
                  <portSpacing port="source_condition" spacing="0"/>
                  <portSpacing port="source_input 1" spacing="0"/>
                  <portSpacing port="source_input 2" spacing="0"/>
                  <portSpacing port="sink_input 1" spacing="0"/>
                  <portSpacing port="sink_input 2" spacing="0"/>
                </process>
                <description align="center" color="transparent" colored="false" width="126">Only replace missings if there are actually any missings.</description>
              </operator>
              <connect from_port="input 1" to_op="Calculate No of Missings" to_port="example set"/>
              <connect from_op="Calculate No of Missings" from_port="example set" to_op="Branch" to_port="input 1"/>
              <connect from_op="Branch" from_port="input 1" to_port="output 1"/>
              <portSpacing port="source_input 1" spacing="0"/>
              <portSpacing port="source_input 2" spacing="0"/>
              <portSpacing port="sink_output 1" spacing="0"/>
              <portSpacing port="sink_output 2" spacing="0"/>
            </process>
            <description align="center" color="transparent" colored="false" width="126">Loop over all nominal attributes.</description>
          </operator>
          <operator activated="true" automodel="EXPORTED" class="select_attributes" compatibility="8.2.000" expanded="true" height="82" name="Remove Dummy" width="90" x="313" y="34">
            <parameter key="attribute_filter_type" value="single"/>
            <parameter key="attribute" value="DUMMY_NOMINAL_ATTRIBUTE_TO_DELETE"/>
            <parameter key="attributes" value=""/>
            <parameter key="use_except_expression" value="false"/>
            <parameter key="value_type" value="attribute_value"/>
            <parameter key="use_value_type_exception" value="false"/>
            <parameter key="except_value_type" value="time"/>
            <parameter key="block_type" value="attribute_block"/>
            <parameter key="use_block_type_exception" value="false"/>
            <parameter key="except_block_type" value="value_matrix_row_start"/>
            <parameter key="invert_selection" value="true"/>
            <parameter key="include_special_attributes" value="false"/>
            <description align="center" color="transparent" colored="false" width="126">Remove dummy attribute again.</description>
          </operator>
          <operator activated="true" automodel="EXPORTED" class="replace_infinite_values" compatibility="8.2.000" expanded="true" height="103" name="Replace Pos Infinite Values" width="90" x="447" y="34">
            <parameter key="return_preprocessing_model" value="false"/>
            <parameter key="create_view" value="false"/>
            <parameter key="attribute_filter_type" value="value_type"/>
            <parameter key="attribute" value=""/>
            <parameter key="attributes" value=""/>
            <parameter key="use_except_expression" value="false"/>
            <parameter key="value_type" value="numeric"/>
            <parameter key="use_value_type_exception" value="false"/>
            <parameter key="except_value_type" value="real"/>
            <parameter key="block_type" value="value_series"/>
            <parameter key="use_block_type_exception" value="false"/>
            <parameter key="except_block_type" value="value_series_end"/>
            <parameter key="invert_selection" value="false"/>
            <parameter key="include_special_attributes" value="true"/>
            <parameter key="default" value="missing"/>
            <list key="columns"/>
            <parameter key="replenish_what" value="positive_infinity"/>
            <description align="center" color="transparent" colored="false" width="126">Replace positive infinity values by missing.</description>
          </operator>
          <operator activated="true" automodel="EXPORTED" class="replace_infinite_values" compatibility="8.2.000" expanded="true" height="103" name="Replace Neg Infinite Values" width="90" x="581" y="34">
            <parameter key="return_preprocessing_model" value="false"/>
            <parameter key="create_view" value="false"/>
            <parameter key="attribute_filter_type" value="value_type"/>
            <parameter key="attribute" value=""/>
            <parameter key="attributes" value=""/>
            <parameter key="use_except_expression" value="false"/>
            <parameter key="value_type" value="numeric"/>
            <parameter key="use_value_type_exception" value="false"/>
            <parameter key="except_value_type" value="real"/>
            <parameter key="block_type" value="value_series"/>
            <parameter key="use_block_type_exception" value="false"/>
            <parameter key="except_block_type" value="value_series_end"/>
            <parameter key="invert_selection" value="false"/>
            <parameter key="include_special_attributes" value="true"/>
            <parameter key="default" value="missing"/>
            <list key="columns"/>
            <parameter key="replenish_what" value="negative_infinity"/>
            <description align="center" color="transparent" colored="false" width="126">Replace negative infinity values by missing.</description>
          </operator>
          <operator activated="true" automodel="EXPORTED" class="replace_missing_values" compatibility="8.2.000" expanded="true" height="103" name="Replace Numerical Missings" width="90" x="715" y="34">
            <parameter key="return_preprocessing_model" value="false"/>
            <parameter key="create_view" value="false"/>
            <parameter key="attribute_filter_type" value="value_type"/>
            <parameter key="attribute" value=""/>
            <parameter key="attributes" value=""/>
            <parameter key="use_except_expression" value="false"/>
            <parameter key="value_type" value="numeric"/>
            <parameter key="use_value_type_exception" value="false"/>
            <parameter key="except_value_type" value="time"/>
            <parameter key="block_type" value="attribute_block"/>
            <parameter key="use_block_type_exception" value="false"/>
            <parameter key="except_block_type" value="value_matrix_row_start"/>
            <parameter key="invert_selection" value="false"/>
            <parameter key="include_special_attributes" value="false"/>
            <parameter key="default" value="average"/>
            <list key="columns"/>
            <description align="center" color="transparent" colored="false" width="126">Replace numerical missings with the average of the column.</description>
          </operator>
          <connect from_port="in 1" to_op="Generate Dummy" to_port="example set input"/>
          <connect from_op="Generate Dummy" from_port="example set output" to_op="Loop Nominal Attributes" to_port="input 1"/>
          <connect from_op="Loop Nominal Attributes" from_port="output 1" to_op="Remove Dummy" to_port="example set input"/>
          <connect from_op="Remove Dummy" from_port="example set output" to_op="Replace Pos Infinite Values" to_port="example set input"/>
          <connect from_op="Replace Pos Infinite Values" from_port="example set output" to_op="Replace Neg Infinite Values" to_port="example set input"/>
          <connect from_op="Replace Neg Infinite Values" from_port="example set output" to_op="Replace Numerical Missings" to_port="example set input"/>
          <connect from_op="Replace Numerical Missings" from_port="example set output" to_port="out 1"/>
          <portSpacing port="source_in 1" spacing="0"/>
          <portSpacing port="source_in 2" spacing="0"/>
          <portSpacing port="sink_out 1" spacing="0"/>
          <portSpacing port="sink_out 2" spacing="0"/>
        </process>
        <description align="center" color="transparent" colored="false" width="126">Replace missing values.</description>
      </operator>
      <operator activated="true" automodel="EXPORTED" class="order_attributes" compatibility="8.2.000" expanded="true" height="82" name="Reorder Attributes" width="90" x="447" y="238">
        <parameter key="sort_mode" value="alphabetically"/>
        <parameter key="attribute_ordering" value=""/>
        <parameter key="use_regular_expressions" value="false"/>
        <parameter key="handle_unmatched" value="append"/>
        <parameter key="sort_direction" value="ascending"/>
        <description align="center" color="transparent" colored="false" width="126">Order columns alphabetically.</description>
      </operator>
      <operator activated="true" automodel="EXPORTED" class="filter_examples" compatibility="8.2.000" expanded="true" height="103" name="Filter Examples" width="90" x="581" y="238">
        <parameter key="parameter_expression" value=""/>
        <parameter key="condition_class" value="no_missing_labels"/>
        <parameter key="invert_filter" value="false"/>
        <list key="filters_list"/>
        <parameter key="filters_logic_and" value="true"/>
        <parameter key="filters_check_metadata" value="true"/>
        <description align="center" color="transparent" colored="false" width="126">Model on cases with label value, apply the model on cases with a missing for the target column.</description>
      </operator>
      <operator activated="true" automodel="EXPORTED" class="sample_stratified" compatibility="8.2.000" expanded="true" height="82" name="Sample (Stratified)" width="90" x="715" y="136">
        <parameter key="sample" value="absolute"/>
        <parameter key="sample_size" value="60000"/>
        <parameter key="sample_ratio" value="0.1"/>
        <parameter key="use_local_random_seed" value="false"/>
        <parameter key="local_random_seed" value="1992"/>
        <description align="center" color="transparent" colored="false" width="126">Sample down to 60,000 examples in case there are more.</description>
      </operator>
      <operator activated="true" automodel="EXPORTED" class="split_data" compatibility="8.2.000" expanded="true" height="103" name="Split Data" width="90" x="849" y="136">
        <enumeration key="partitions">
          <parameter key="ratio" value="0.8"/>
          <parameter key="ratio" value="0.2"/>
        </enumeration>
        <parameter key="sampling_type" value="automatic"/>
        <parameter key="use_local_random_seed" value="true"/>
        <parameter key="local_random_seed" value="1992"/>
        <description align="center" color="transparent" colored="false" width="126">Split of a validation set.</description>
      </operator>
      <operator activated="true" automodel="EXPORTED" class="multiply" compatibility="8.2.000" expanded="true" height="124" name="Multiply Training" width="90" x="983" y="136">
        <description align="center" color="transparent" colored="false" width="126">Copy data for simulator.</description>
      </operator>
      <operator activated="true" automodel="EXPORTED" class="concurrency:optimize_parameters_grid" compatibility="8.2.000" expanded="true" height="124" name="Optimize Parameters (Grid)" width="90" x="1117" y="34">
        <list key="parameters">
          <parameter key="Gradient Boosted Trees.number_of_trees" value="[20;140;3;linear]"/>
          <parameter key="Gradient Boosted Trees.maximal_depth" value="2,4,7"/>
        </list>
        <parameter key="error_handling" value="fail on error"/>
        <parameter key="log_performance" value="false"/>
        <parameter key="log_all_criteria" value="false"/>
        <parameter key="synchronize" value="false"/>
        <parameter key="enable_parallel_execution" value="true"/>
        <process expanded="true">
          <operator activated="true" automodel="EXPORTED" class="concurrency:cross_validation" compatibility="8.2.000" expanded="true" height="145" name="Cross Validation" width="90" x="45" y="34">
            <parameter key="split_on_batch_attribute" value="false"/>
            <parameter key="leave_one_out" value="false"/>
            <parameter key="number_of_folds" value="3"/>
            <parameter key="sampling_type" value="automatic"/>
            <parameter key="use_local_random_seed" value="true"/>
            <parameter key="local_random_seed" value="1992"/>
            <parameter key="enable_parallel_execution" value="true"/>
            <process expanded="true">
              <operator activated="true" automodel="EXPORTED" class="h2o:gradient_boosted_trees" compatibility="8.2.000" expanded="true" height="103" name="Gradient Boosted Trees" width="90" x="45" y="34">
                <parameter key="number_of_trees" value="20"/>
                <parameter key="reproducible" value="true"/>
                <parameter key="maximum_number_of_threads" value="1"/>
                <parameter key="use_local_random_seed" value="true"/>
                <parameter key="local_random_seed" value="1992"/>
                <parameter key="maximal_depth" value="5"/>
                <parameter key="min_rows" value="10.0"/>
                <parameter key="min_split_improvement" value="0.0"/>
                <parameter key="number_of_bins" value="20"/>
                <parameter key="learning_rate" value="0.1"/>
                <parameter key="sample_rate" value="1.0"/>
                <parameter key="distribution" value="AUTO"/>
                <parameter key="early_stopping" value="false"/>
                <parameter key="stopping_rounds" value="1"/>
                <parameter key="stopping_metric" value="AUTO"/>
                <parameter key="stopping_tolerance" value="0.001"/>
                <parameter key="max_runtime_seconds" value="0"/>
                <list key="expert_parameters"/>
              </operator>
              <connect from_port="training set" to_op="Gradient Boosted Trees" to_port="training set"/>
              <connect from_op="Gradient Boosted Trees" from_port="model" to_port="model"/>
              <portSpacing port="source_training set" spacing="0"/>
              <portSpacing port="sink_model" spacing="0"/>
              <portSpacing port="sink_through 1" spacing="0"/>
            </process>
            <process expanded="true">
              <operator activated="true" automodel="EXPORTED" class="apply_model" compatibility="8.2.000" expanded="true" height="82" name="Apply Model" width="90" x="45" y="34">
                <list key="application_parameters"/>
                <parameter key="create_view" value="false"/>
              </operator>
              <operator activated="true" automodel="EXPORTED" class="performance_binominal_classification" compatibility="8.2.000" expanded="true" height="82" name="Inner Performance" width="90" x="179" y="34">
                <parameter key="main_criterion" value="accuracy"/>
                <parameter key="accuracy" value="true"/>
                <parameter key="classification_error" value="true"/>
                <parameter key="kappa" value="false"/>
                <parameter key="AUC (optimistic)" value="false"/>
                <parameter key="AUC" value="true"/>
                <parameter key="AUC (pessimistic)" value="false"/>
                <parameter key="precision" value="true"/>
                <parameter key="recall" value="true"/>
                <parameter key="lift" value="false"/>
                <parameter key="fallout" value="false"/>
                <parameter key="f_measure" value="true"/>
                <parameter key="false_positive" value="false"/>
                <parameter key="false_negative" value="false"/>
                <parameter key="true_positive" value="false"/>
                <parameter key="true_negative" value="false"/>
                <parameter key="sensitivity" value="true"/>
                <parameter key="specificity" value="true"/>
                <parameter key="youden" value="false"/>
                <parameter key="positive_predictive_value" value="false"/>
                <parameter key="negative_predictive_value" value="false"/>
                <parameter key="psep" value="false"/>
                <parameter key="skip_undefined_labels" value="true"/>
                <parameter key="use_example_weights" value="true"/>
              </operator>
              <connect from_port="model" to_op="Apply Model" to_port="model"/>
              <connect from_port="test set" to_op="Apply Model" to_port="unlabelled data"/>
              <connect from_op="Apply Model" from_port="labelled data" to_op="Inner Performance" to_port="labelled data"/>
              <connect from_op="Inner Performance" from_port="performance" to_port="performance 1"/>
              <portSpacing port="source_model" spacing="0"/>
              <portSpacing port="source_test set" spacing="0"/>
              <portSpacing port="source_through 1" spacing="0"/>
              <portSpacing port="sink_test set results" spacing="0"/>
              <portSpacing port="sink_performance 1" spacing="0"/>
              <portSpacing port="sink_performance 2" spacing="0"/>
            </process>
            <description align="center" color="transparent" colored="false" width="126">Cross-validate the model and build final model on complete data.</description>
          </operator>
          <operator activated="true" automodel="EXPORTED" class="log" compatibility="8.2.000" expanded="true" height="82" name="Log Performances" width="90" x="179" y="85">
            <list key="log">
              <parameter key="Number of Trees" value="operator.Gradient Boosted Trees.parameter.number_of_trees"/>
              <parameter key="Maximal Depth" value="operator.Gradient Boosted Trees.parameter.maximal_depth"/>
              <parameter key="Performance" value="operator.Cross Validation.value.performance main criterion"/>
            </list>
            <parameter key="sorting_type" value="none"/>
            <parameter key="sorting_k" value="100"/>
            <parameter key="persistent" value="false"/>
            <description align="center" color="transparent" colored="false" width="126">Log the performance for all parameter combinations.</description>
          </operator>
          <connect from_port="input 1" to_op="Cross Validation" to_port="example set"/>
          <connect from_op="Cross Validation" from_port="model" to_port="model"/>
          <connect from_op="Cross Validation" from_port="performance 1" to_op="Log Performances" to_port="through 1"/>
          <connect from_op="Log Performances" from_port="through 1" to_port="performance"/>
          <portSpacing port="source_input 1" spacing="0"/>
          <portSpacing port="source_input 2" spacing="0"/>
          <portSpacing port="sink_performance" spacing="0"/>
          <portSpacing port="sink_model" spacing="0"/>
          <portSpacing port="sink_output 1" spacing="0"/>
        </process>
        <description align="center" color="transparent" colored="false" width="126">Find optimal parameters.</description>
      </operator>
      <operator activated="true" automodel="EXPORTED" class="multiply" compatibility="8.2.000" expanded="true" height="124" name="Multiply Validation" width="90" x="983" y="340">
        <description align="center" color="transparent" colored="false" width="126">Copy validation data.</description>
      </operator>
      <operator activated="true" automodel="EXPORTED" class="model_simulator:model_simulator" compatibility="8.2.000" expanded="true" height="103" name="Model Simulator" width="90" x="1318" y="34">
        <description align="center" color="transparent" colored="false" width="126">Create model simulator.</description>
      </operator>
      <operator activated="true" automodel="EXPORTED" class="multiply" compatibility="8.2.000" expanded="true" height="124" name="Multiply Model" width="90" x="1452" y="187">
        <description align="center" color="transparent" colored="false" width="126">Copy model.</description>
      </operator>
      <operator activated="true" automodel="EXPORTED" class="apply_model" compatibility="8.2.000" expanded="true" height="82" name="Apply Optimized Model" width="90" x="1586" y="85">
        <list key="application_parameters"/>
        <parameter key="create_view" value="false"/>
        <description align="center" color="transparent" colored="false" width="126">Apply optimized model on validation set.</description>
      </operator>
      <operator activated="true" automodel="EXPORTED" class="performance_binominal_classification" compatibility="8.2.000" expanded="true" height="82" name="Performance" width="90" x="1720" y="34">
        <parameter key="main_criterion" value="accuracy"/>
        <parameter key="accuracy" value="true"/>
        <parameter key="classification_error" value="true"/>
        <parameter key="kappa" value="false"/>
        <parameter key="AUC (optimistic)" value="false"/>
        <parameter key="AUC" value="true"/>
        <parameter key="AUC (pessimistic)" value="false"/>
        <parameter key="precision" value="true"/>
        <parameter key="recall" value="true"/>
        <parameter key="lift" value="false"/>
        <parameter key="fallout" value="false"/>
        <parameter key="f_measure" value="true"/>
        <parameter key="false_positive" value="false"/>
        <parameter key="false_negative" value="false"/>
        <parameter key="true_positive" value="false"/>
        <parameter key="true_negative" value="false"/>
        <parameter key="sensitivity" value="true"/>
        <parameter key="specificity" value="true"/>
        <parameter key="youden" value="false"/>
        <parameter key="positive_predictive_value" value="false"/>
        <parameter key="negative_predictive_value" value="false"/>
        <parameter key="psep" value="false"/>
        <parameter key="skip_undefined_labels" value="true"/>
        <parameter key="use_example_weights" value="true"/>
        <description align="center" color="transparent" colored="false" width="126">Performance on validation set.</description>
      </operator>
      <operator activated="true" automodel="EXPORTED" class="model_simulator:explain_predictions" compatibility="8.2.000" expanded="true" height="103" name="Explain Predictions" width="90" x="1586" y="289">
        <parameter key="maximal explaining attributes" value="3"/>
        <parameter key="local sample size" value="500"/>
        <description align="center" color="transparent" colored="false" width="126">Create predictions for cases without value and add explanations for predictions.</description>
      </operator>
      <operator activated="true" automodel="EXPORTED" class="log_to_data" compatibility="8.2.000" expanded="true" height="82" name="Log to Data" width="90" x="1586" y="697">
        <parameter key="log_name" value="Log Performances"/>
        <description align="center" color="transparent" colored="false" width="126">Deliver all performances.</description>
      </operator>
      <operator activated="true" automodel="EXPORTED" class="model_simulator:lift_chart" compatibility="8.2.000" expanded="true" height="82" name="Create Lift Chart" width="90" x="1586" y="544">
        <parameter key="target class" value="Positive"/>
        <description align="center" color="transparent" colored="false" width="126">Create lift chart.</description>
      </operator>
      <connect from_op="Retrieve Data" from_port="output" to_op="Preprocessing" to_port="in 1"/>
      <connect from_op="Preprocessing" from_port="out 1" to_op="Replace Missing Values" to_port="in 1"/>
      <connect from_op="Replace Missing Values" from_port="out 1" to_op="Reorder Attributes" to_port="example set input"/>
      <connect from_op="Reorder Attributes" from_port="example set output" to_op="Filter Examples" to_port="example set input"/>
      <connect from_op="Filter Examples" from_port="example set output" to_op="Sample (Stratified)" to_port="example set input"/>
      <connect from_op="Filter Examples" from_port="unmatched example set" to_op="Explain Predictions" to_port="test data"/>
      <connect from_op="Sample (Stratified)" from_port="example set output" to_op="Split Data" to_port="example set"/>
      <connect from_op="Split Data" from_port="partition 1" to_op="Multiply Training" to_port="input"/>
      <connect from_op="Split Data" from_port="partition 2" to_op="Multiply Validation" to_port="input"/>
      <connect from_op="Multiply Training" from_port="output 1" to_op="Optimize Parameters (Grid)" to_port="input 1"/>
      <connect from_op="Multiply Training" from_port="output 2" to_op="Model Simulator" to_port="training data"/>
      <connect from_op="Multiply Training" from_port="output 3" to_op="Explain Predictions" to_port="training data"/>
      <connect from_op="Optimize Parameters (Grid)" from_port="model" to_op="Model Simulator" to_port="model"/>
      <connect from_op="Optimize Parameters (Grid)" from_port="parameter set" to_port="result 2"/>
      <connect from_op="Multiply Validation" from_port="output 1" to_op="Model Simulator" to_port="test data"/>
      <connect from_op="Multiply Validation" from_port="output 2" to_op="Create Lift Chart" to_port="test data"/>
      <connect from_op="Multiply Validation" from_port="output 3" to_op="Apply Optimized Model" to_port="unlabelled data"/>
      <connect from_op="Model Simulator" from_port="simulator output" to_port="result 3"/>
      <connect from_op="Model Simulator" from_port="model output" to_op="Multiply Model" to_port="input"/>
      <connect from_op="Multiply Model" from_port="output 1" to_op="Apply Optimized Model" to_port="model"/>
      <connect from_op="Multiply Model" from_port="output 2" to_op="Explain Predictions" to_port="model"/>
      <connect from_op="Multiply Model" from_port="output 3" to_op="Create Lift Chart" to_port="model"/>
      <connect from_op="Apply Optimized Model" from_port="labelled data" to_op="Performance" to_port="labelled data"/>
      <connect from_op="Apply Optimized Model" from_port="model" to_port="result 4"/>
      <connect from_op="Performance" from_port="performance" to_port="result 1"/>
      <connect from_op="Explain Predictions" from_port="visualization output" to_port="result 5"/>
      <connect from_op="Explain Predictions" from_port="example set output" to_port="result 6"/>
      <connect from_op="Log to Data" from_port="exampleSet" to_port="result 8"/>
      <connect from_op="Create Lift Chart" from_port="lift chart" to_port="result 7"/>
      <portSpacing port="source_input 1" spacing="0"/>
      <portSpacing port="sink_result 1" spacing="0"/>
      <portSpacing port="sink_result 2" spacing="42"/>
      <portSpacing port="sink_result 3" spacing="0"/>
      <portSpacing port="sink_result 4" spacing="0"/>
      <portSpacing port="sink_result 5" spacing="84"/>
      <portSpacing port="sink_result 6" spacing="0"/>
      <portSpacing port="sink_result 7" spacing="252"/>
      <portSpacing port="sink_result 8" spacing="84"/>
      <portSpacing port="sink_result 9" spacing="0"/>
      <description align="left" color="yellow" colored="false" height="175" resized="true" width="481" x="372" y="477">Results:&lt;br&gt;1. Performance from validation set (split off before parameter optimization)&lt;br&gt;2. Optimal parameters&lt;br&gt;3. Model simulator&lt;br&gt;4. Model&lt;br&gt;5. Predicted data with explanations viz (only if the data had missing labels)&lt;br&gt;6. Predicted data with explanations table (only if the data had missing labels)&lt;br&gt;7. Lift chart&lt;br&gt;8. All performances from 3-fold cross-validation in parameter optimization</description>
    </process>
  </operator>
</process>

How can I check performance for testing dataset from Auto Model process?