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how to reopen results of an auto model after closing Rapidminer

1338773patti1338773patti Member Posts: 4 Contributor I
edited June 2019 in Help

as the title says.
I would like to open the results I got from an Auto model. I ran a Deep learning model. got some brilliant results, then saved the process, but how do I save the results to reopen them later??? Do i have to rerun the complete process again?? 

Sorry if this topic already excisted I can't find it anywhere. 

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Answers

  • rfuentealbarfuentealba Moderator, RapidMiner Certified Analyst, Member, University Professor Posts: 515   Unicorn

    Hi @1338773patti,

     

    I don't know a way to save results. There are some things you can do so you can reuse your training methods, though:

     

    1. Split your process in two, maybe three.
      1. The first one, namely 01 Training can perform everything up to validation. Instead of Apply Model, though, you should use a Store parameter to store the result of your algorithm, though.
      2. The second one, namely 02 Running needs to Retrieve the result of your algorithm, and that should be connected to the Apply Model operator.
    2. Run your 01 Training process everytime your training data changes.
    3. Run your 02 Running process everytime you have new data (to process it against your latest trained model).

    You can virtually store anything you want using the Store operator, as long as it can be converted internally into an IOObject, so you might want to place a Store operator just before any endpoint in your process, like here:

     

    Screen Shot 2018-10-24 at 01.36.10.png

     

    Now, don't be scared by IOObjects. These are the structures used internally by RapidMiner to store data, functions, models, etc. Just remember that these can be Store'd and Retrieve'd.

     

    Here is a demo, using RapidMiner Studio and the classic Titanic Dataset with a Deep Learning algorithm that saves results before displaying.

     

    <?xml version="1.0" encoding="UTF-8"?><process version="9.0.002">
    <context>
    <input/>
    <output/>
    <macros/>
    </context>
    <operator activated="true" class="process" compatibility="9.0.002" expanded="true" name="Process" origin="EXPORTED_AUTOMODEL">
    <process expanded="true">
    <operator activated="true" class="retrieve" compatibility="9.0.002" expanded="true" height="68" name="Retrieve Data" origin="EXPORTED_AUTOMODEL" width="90" x="45" y="238">
    <parameter key="repository_entry" value="//Samples/data/Titanic Training"/>
    <description align="center" color="transparent" colored="false" width="126">Load data.</description>
    </operator>
    <operator activated="true" class="subprocess" compatibility="9.0.002" expanded="true" height="82" name="Preprocessing" origin="EXPORTED_AUTOMODEL" width="90" x="179" y="238">
    <process expanded="true">
    <operator activated="true" class="select_subprocess" compatibility="9.0.002" expanded="true" height="82" name="Define Target?" origin="EXPORTED_AUTOMODEL" 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" class="set_role" compatibility="9.0.002" expanded="true" height="82" name="Define Target" origin="EXPORTED_AUTOMODEL" width="90" x="45" y="34">
    <parameter key="attribute_name" value="Survived"/>
    <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" class="select_subprocess" compatibility="9.0.002" expanded="true" height="82" name="Should Discretize?" origin="EXPORTED_AUTOMODEL" width="90" x="179" y="34">
    <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" class="discretize_by_bins" compatibility="9.0.002" expanded="true" height="103" name="Binning" origin="EXPORTED_AUTOMODEL" width="90" x="45" y="34">
    <parameter key="attribute_filter_type" value="single"/>
    <parameter key="attribute" value="Age"/>
    <parameter key="include_special_attributes" value="true"/>
    <parameter key="range_name_type" value="short"/>
    <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" class="discretize_by_frequency" compatibility="9.0.002" expanded="true" height="103" name="Frequency" origin="EXPORTED_AUTOMODEL" width="90" x="45" y="34">
    <parameter key="attribute_filter_type" value="single"/>
    <parameter key="attribute" value="Age"/>
    <parameter key="include_special_attributes" value="true"/>
    <parameter key="range_name_type" value="short"/>
    <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" class="select_subprocess" compatibility="9.0.002" expanded="true" height="82" name="Map Values?" origin="EXPORTED_AUTOMODEL" width="90" x="313" y="34">
    <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" class="map" compatibility="9.0.002" expanded="true" height="82" name="Map Values" origin="EXPORTED_AUTOMODEL" width="90" x="45" y="34">
    <parameter key="attribute_filter_type" value="single"/>
    <parameter key="attribute" value="Survived"/>
    <parameter key="include_special_attributes" value="true"/>
    <list key="value_mappings"/>
    <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" class="select_subprocess" compatibility="9.0.002" expanded="true" height="82" name="Positive Class?" origin="EXPORTED_AUTOMODEL" 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" class="nominal_to_binominal" compatibility="9.0.002" expanded="true" height="103" name="Nominal to Binominal" origin="EXPORTED_AUTOMODEL" width="90" x="45" y="34">
    <parameter key="attribute_filter_type" value="single"/>
    <parameter key="attribute" value="Survived"/>
    <parameter key="include_special_attributes" value="true"/>
    <description align="center" color="transparent" colored="false" width="126">Make sure that target is binary for positive class mapping.</description>
    </operator>
    <operator activated="true" class="remap_binominals" compatibility="9.0.002" expanded="true" height="82" name="Define Positive Class" origin="EXPORTED_AUTOMODEL" width="90" x="179" y="34">
    <parameter key="attribute_filter_type" value="single"/>
    <parameter key="attribute" value="Survived"/>
    <parameter key="include_special_attributes" value="true"/>
    <parameter key="negative_value" value="No"/>
    <parameter key="positive_value" value="Yes"/>
    <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" class="select_subprocess" compatibility="9.0.002" expanded="true" height="82" name="Remove Columns?" origin="EXPORTED_AUTOMODEL" width="90" x="581" 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" class="select_attributes" compatibility="9.0.002" expanded="true" height="82" name="Remove Columns" origin="EXPORTED_AUTOMODEL" width="90" x="45" y="34">
    <parameter key="attribute_filter_type" value="regular_expression"/>
    <parameter key="regular_expression" value="\QNo of Siblings or Spouses on Board\E|\QNo of Parents or Children on Board\E|\QPassenger Fare\E"/>
    <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" class="subprocess" compatibility="9.0.002" expanded="true" height="82" name="Unify Value Types" origin="EXPORTED_AUTOMODEL" width="90" x="715" y="34">
    <process expanded="true">
    <operator activated="true" class="select_attributes" compatibility="9.0.002" expanded="true" height="82" name="Remove Dates" origin="EXPORTED_AUTOMODEL" width="90" x="45" y="34">
    <parameter key="attribute_filter_type" value="value_type"/>
    <parameter key="value_type" value="date_time"/>
    <parameter key="invert_selection" value="true"/>
    <description align="center" color="transparent" colored="false" width="126">Remove all date columns.</description>
    </operator>
    <operator activated="true" class="nominal_to_text" compatibility="9.0.002" expanded="true" height="82" name="Nominal to Text" origin="EXPORTED_AUTOMODEL" width="90" x="179" y="34">
    <parameter key="attribute_filter_type" value="value_type"/>
    <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" class="text_to_nominal" compatibility="9.0.002" expanded="true" height="82" name="Text to Nominal" origin="EXPORTED_AUTOMODEL" width="90" x="313" y="34">
    <parameter key="attribute_filter_type" value="value_type"/>
    <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" class="numerical_to_real" compatibility="9.0.002" expanded="true" height="82" name="Numerical to Real" origin="EXPORTED_AUTOMODEL" width="90" x="447" y="34">
    <parameter key="attribute_filter_type" value="value_type"/>
    <parameter key="use_value_type_exception" value="true"/>
    <parameter key="except_value_type" value="integer"/>
    <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" class="subprocess" compatibility="9.0.002" expanded="true" height="82" name="Replace Missing Values" origin="EXPORTED_AUTOMODEL" width="90" x="313" y="238">
    <process expanded="true">
    <operator activated="true" class="generate_attributes" compatibility="9.0.002" expanded="true" height="82" name="Generate Dummy" origin="EXPORTED_AUTOMODEL" width="90" x="45" y="34">
    <list key="function_descriptions">
    <parameter key="DUMMY_NOMINAL_ATTRIBUTE_TO_DELETE" value="&quot;dummy&quot;"/>
    </list>
    <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" class="concurrency:loop_attributes" compatibility="8.2.000" expanded="true" height="82" name="Loop Nominal Attributes" origin="EXPORTED_AUTOMODEL" width="90" x="179" y="34">
    <parameter key="attribute_filter_type" value="value_type"/>
    <parameter key="value_type" value="nominal"/>
    <parameter key="attribute_name_macro" value="nominal_attribute"/>
    <parameter key="reuse_results" value="true"/>
    <process expanded="true">
    <operator activated="true" class="extract_macro" compatibility="9.0.002" expanded="true" height="68" name="Calculate No of Missings" origin="EXPORTED_AUTOMODEL" 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" class="branch" compatibility="9.0.002" expanded="true" height="103" name="Branch" origin="EXPORTED_AUTOMODEL" width="90" x="179" y="34">
    <parameter key="condition_type" value="expression"/>
    <parameter key="expression" value="eval(%{no_missings})==0"/>
    <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" class="replace_missing_values" compatibility="9.0.002" expanded="true" height="103" name="Replace Nominal Missings" origin="EXPORTED_AUTOMODEL" width="90" x="112" y="34">
    <parameter key="attribute_filter_type" value="single"/>
    <parameter key="attribute" value="%{nominal_attribute}"/>
    <parameter key="value_type" value="nominal"/>
    <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" class="select_attributes" compatibility="9.0.002" expanded="true" height="82" name="Remove Dummy" origin="EXPORTED_AUTOMODEL" width="90" x="313" y="34">
    <parameter key="attribute_filter_type" value="single"/>
    <parameter key="attribute" value="DUMMY_NOMINAL_ATTRIBUTE_TO_DELETE"/>
    <parameter key="invert_selection" value="true"/>
    <description align="center" color="transparent" colored="false" width="126">Remove dummy attribute again.</description>
    </operator>
    <operator activated="true" class="replace_infinite_values" compatibility="9.0.002" expanded="true" height="103" name="Replace Pos Infinite Values" origin="EXPORTED_AUTOMODEL" width="90" x="447" y="34">
    <parameter key="attribute_filter_type" value="value_type"/>
    <parameter key="include_special_attributes" value="true"/>
    <parameter key="default" value="missing"/>
    <list key="columns"/>
    <description align="center" color="transparent" colored="false" width="126">Replace positive infinity values by missing.</description>
    </operator>
    <operator activated="true" class="replace_infinite_values" compatibility="9.0.002" expanded="true" height="103" name="Replace Neg Infinite Values" origin="EXPORTED_AUTOMODEL" width="90" x="581" y="34">
    <parameter key="attribute_filter_type" value="value_type"/>
    <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" class="replace_missing_values" compatibility="9.0.002" expanded="true" height="103" name="Replace Numerical Missings" origin="EXPORTED_AUTOMODEL" width="90" x="715" y="34">
    <parameter key="attribute_filter_type" value="value_type"/>
    <parameter key="value_type" value="numeric"/>
    <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" class="order_attributes" compatibility="9.0.002" expanded="true" height="82" name="Reorder Attributes" origin="EXPORTED_AUTOMODEL" width="90" x="447" y="238">
    <parameter key="sort_mode" value="alphabetically"/>
    <description align="center" color="transparent" colored="false" width="126">Order columns alphabetically.</description>
    </operator>
    <operator activated="true" class="filter_examples" compatibility="9.0.002" expanded="true" height="103" name="Filter Examples" origin="EXPORTED_AUTOMODEL" width="90" x="581" y="238">
    <parameter key="condition_class" value="no_missing_labels"/>
    <list key="filters_list"/>
    <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" class="sample_stratified" compatibility="9.0.002" expanded="true" height="82" name="Sample (Stratified)" origin="EXPORTED_AUTOMODEL" width="90" x="715" y="34">
    <parameter key="sample_size" value="250000"/>
    <description align="center" color="transparent" colored="false" width="126">Sample down to 250,000 examples in case there are more.</description>
    </operator>
    <operator activated="true" class="split_data" compatibility="9.0.002" expanded="true" height="103" name="Split Data" origin="EXPORTED_AUTOMODEL" width="90" x="849" y="85">
    <enumeration key="partitions">
    <parameter key="ratio" value="0.8"/>
    <parameter key="ratio" value="0.2"/>
    </enumeration>
    <parameter key="use_local_random_seed" value="true"/>
    <description align="center" color="transparent" colored="false" width="126">Split of a validation set.</description>
    </operator>
    <operator activated="true" class="h2o:deep_learning" compatibility="9.0.000" expanded="true" height="82" name="Deep Learning" origin="EXPORTED_AUTOMODEL" width="90" x="983" y="34">
    <enumeration key="hidden_layer_sizes">
    <parameter key="hidden_layer_sizes" value="50"/>
    <parameter key="hidden_layer_sizes" value="50"/>
    </enumeration>
    <enumeration key="hidden_dropout_ratios"/>
    <parameter key="reproducible_(uses_1_thread)" value="true"/>
    <parameter key="use_local_random_seed" value="true"/>
    <list key="expert_parameters"/>
    <list key="expert_parameters_"/>
    <description align="center" color="transparent" colored="false" width="126">Train model.</description>
    </operator>
    <operator activated="true" class="multiply" compatibility="9.0.002" expanded="true" height="103" name="Multiply Training" origin="EXPORTED_AUTOMODEL" width="90" x="1117" y="85">
    <description align="center" color="transparent" colored="false" width="126">Copy training data.</description>
    </operator>
    <operator activated="true" class="multiply" compatibility="9.0.002" expanded="true" height="124" name="Multiply Validation" origin="EXPORTED_AUTOMODEL" width="90" x="1117" y="238">
    <description align="center" color="transparent" colored="false" width="126">Copy validation data.</description>
    </operator>
    <operator activated="true" class="model_simulator:model_simulator" compatibility="9.0.001" expanded="true" height="103" name="Model Simulator" origin="EXPORTED_AUTOMODEL" width="90" x="1251" y="34">
    <description align="center" color="transparent" colored="false" width="126">Create model simulator.</description>
    </operator>
    <operator activated="true" class="store" compatibility="9.0.002" expanded="true" height="68" name="Store Simulator" width="90" x="1854" y="34">
    <parameter key="repository_entry" value="//Local Repository/simulator"/>
    </operator>
    <operator activated="true" class="multiply" compatibility="9.0.002" expanded="true" height="124" name="Multiply Model" origin="EXPORTED_AUTOMODEL" width="90" x="1385" y="85">
    <description align="center" color="transparent" colored="false" width="126">Copy model.</description>
    </operator>
    <operator activated="true" class="apply_model" compatibility="9.0.002" expanded="true" height="82" name="Apply Model" origin="EXPORTED_AUTOMODEL" width="90" x="1519" y="85">
    <list key="application_parameters"/>
    <description align="center" color="transparent" colored="false" width="126">Apply model on validation set.</description>
    </operator>
    <operator activated="true" class="store" compatibility="9.0.002" expanded="true" height="68" name="Store Examples" width="90" x="1988" y="238">
    <parameter key="repository_entry" value="//Local Repository/examples"/>
    </operator>
    <operator activated="true" class="performance_binominal_classification" compatibility="9.0.002" expanded="true" height="82" name="Performance" origin="EXPORTED_AUTOMODEL" width="90" x="1653" y="85">
    <parameter key="main_criterion" value="accuracy"/>
    <parameter key="classification_error" value="true"/>
    <parameter key="AUC" value="true"/>
    <parameter key="precision" value="true"/>
    <parameter key="recall" value="true"/>
    <parameter key="f_measure" value="true"/>
    <parameter key="sensitivity" value="true"/>
    <parameter key="specificity" value="true"/>
    <description align="center" color="transparent" colored="false" width="126">Performance on validation set.</description>
    </operator>
    <operator activated="true" class="store" compatibility="9.0.002" expanded="true" height="68" name="Store Performance" width="90" x="1988" y="136">
    <parameter key="repository_entry" value="//Local Repository/perf"/>
    </operator>
    <operator activated="true" class="model_simulator:explain_predictions" compatibility="9.0.001" expanded="true" height="103" name="Explain Predictions" origin="EXPORTED_AUTOMODEL" width="90" x="1519" y="238">
    <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" class="model_simulator:lift_chart" compatibility="9.0.001" expanded="true" height="82" name="Create Lift Chart" origin="EXPORTED_AUTOMODEL" width="90" x="1519" y="493">
    <parameter key="target class" value="Yes"/>
    <description align="center" color="transparent" colored="false" width="126">Create lift chart.</description>
    </operator>
    <operator activated="true" class="store" compatibility="9.0.002" expanded="true" height="68" name="Store Lift Chart" width="90" x="1988" y="544">
    <parameter key="repository_entry" value="//Local Repository/liftchart"/>
    </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="Deep Learning" to_port="training set"/>
    <connect from_op="Split Data" from_port="partition 2" to_op="Multiply Validation" to_port="input"/>
    <connect from_op="Deep Learning" from_port="model" to_op="Model Simulator" to_port="model"/>
    <connect from_op="Deep Learning" from_port="exampleSet" to_op="Multiply Training" to_port="input"/>
    <connect from_op="Multiply Training" from_port="output 1" to_op="Model Simulator" to_port="training data"/>
    <connect from_op="Multiply Training" from_port="output 2" to_op="Explain Predictions" to_port="training data"/>
    <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="Apply Model" to_port="unlabelled data"/>
    <connect from_op="Multiply Validation" from_port="output 3" to_op="Create Lift Chart" to_port="test data"/>
    <connect from_op="Model Simulator" from_port="simulator output" to_op="Store Simulator" to_port="input"/>
    <connect from_op="Model Simulator" from_port="model output" to_op="Multiply Model" to_port="input"/>
    <connect from_op="Store Simulator" from_port="through" to_port="result 1"/>
    <connect from_op="Multiply Model" from_port="output 1" to_op="Apply 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 Model" from_port="labelled data" to_op="Performance" to_port="labelled data"/>
    <connect from_op="Apply Model" from_port="model" to_op="Store Examples" to_port="input"/>
    <connect from_op="Store Examples" from_port="through" to_port="result 3"/>
    <connect from_op="Performance" from_port="performance" to_op="Store Performance" to_port="input"/>
    <connect from_op="Store Performance" from_port="through" to_port="result 2"/>
    <connect from_op="Explain Predictions" from_port="visualization output" to_port="result 4"/>
    <connect from_op="Explain Predictions" from_port="example set output" to_port="result 5"/>
    <connect from_op="Create Lift Chart" from_port="lift chart" to_op="Store Lift Chart" to_port="input"/>
    <connect from_op="Store Lift Chart" from_port="through" to_port="result 6"/>
    <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="189"/>
    <portSpacing port="sink_result 4" spacing="63"/>
    <portSpacing port="sink_result 5" spacing="0"/>
    <portSpacing port="sink_result 6" spacing="105"/>
    <portSpacing port="sink_result 7" spacing="0"/>
    <description align="left" color="yellow" colored="false" height="140" resized="true" width="468" x="702" y="417">Results:&lt;br&gt;1. Model simulator&lt;br&gt;2. Performance from validation set (split off before modeling)&lt;br&gt;3. Model&lt;br&gt;4. Predicted data with explanation viz (only if the data had missing labels)&lt;br&gt;5. Predicted data with explanation table (only if the data had missing labels)&lt;br&gt;6. Lift chart</description>
    </process>
    </operator>
    </process>

     

    Hope this helps,

     

    Rodrigo.

    sgenzer1338773patti
  • 1338773patti1338773patti Member Posts: 4 Contributor I

    First of all, thank you for your quick and very extensive reply, 

     

    I do know you can rerun the process but that takes almost as long as first auto modeling. 
    so I was looking for a way to save the results so I can, when I close and reopen rapidminer,  work on the simulation and the optimization again. 
    Also I whas looking how to save the results to use in a presentation or a report. 
    I am a student and have to include every little step of the process in my reports. 

  • rfuentealbarfuentealba Moderator, RapidMiner Certified Analyst, Member, University Professor Posts: 515   Unicorn
    • First of all, thank you for your quick and very extensive reply

    My pleasure. We are here to help!

    • I do know you can rerun the process but that takes almost as long as first auto modeling. 

    Unfortunately yes, but that's the best use case for most of us.

     

    • so I was looking for a way to save the results so I can, when I close and reopen rapidminer, work on the simulation and the optimization again.

    You can save the simulation and the optimized work, that was what I suggested in the first place.

     

    • Also I was looking how to save the results to use in a presentation or a report. I am a student and have to include every little step of the process in my reports. 

    I have three suggestions here, both of these require that you run your Auto ModelOpen the Process and save it at the end of your run. The idea behind Auto Model is that you can accelerate the process of running your models, but you are then encouraged to modify it by yourself to suit your needs. 

     

    Take one of these:

     

    1. Easy method: document each step by adding quick notes straight on the RapidMiner repository. You can then share a large screenshot.
    2. Less easy method: record a video using Camtasia. No, just kidding. Add breakpoints before and after every important/interesting step you want to document, so you can build screenshots on intermediate results. To do so, you can just do a secondary click on each box.
    3. Hard (using storage) method: instead of putting breakpoints, use the Store operator as I already suggested, your results will be readily available on a click. Just make sure you create a Results folder in your Local Repository and save your results with a different name on that folder. To work with the simulator, you can then go to the Local Repository, to the Results folder and double click the simulator.

    Again, take a look at the XML process that I have shared with you. You can create a new Process, open the XML panel in View > Show Panel > XML, paste the entire XML result and click on the green tick on the top, be back at the Process panel and your process will run seamlessly if you have RapidMiner 9. Look at the end of the process, where all those Store operators are. These will save data for you on the root of your Local Repository, so if you run it, you can see how did I do that.

     

    All the best,

     

    Rodrigo.

    sgenzer
  • sgenzersgenzer 12Administrator, Moderator, Employee, RapidMiner Certified Analyst, Community Manager, Member, University Professor, PM Moderator Posts: 2,954  Community Manager

    this sounds like an Auto Model feature request to me...copying @IngoRM

     

    Scott

     

  • figueroajcfigueroajc Member Posts: 5 Contributor I
    Yes, I ran into this same issue.  Automodel took a couple of hours to run and generate a nice comparison between several different algorithms, then I found out I lost the comparison results since they are not saved anywhere and the export button only exports small bits and pieces of it at a time
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