Remove correlated features from training set and apply the same features to test set

Andy3

Hello all,

I just wondering how you achieve to remove pairwise correlated features from your training set (using the Remove Correlated Attributes operator) and apply the same features to your test set? If I should compare this operation to something I think about the "Apply feature set" (as exists for the features selection operator) or somewhat OHE and the Preprocessing model output. See screenshot below of the process. I have normally these two training and test preprocessing operations in two different processes.

Thanks for your help.

MartinLiebig

Hi @Andy3,

you usually don't need to do it. Keep in mind that Apply Model is ignoring additional attributes.

Best,

Martin

MartinLiebig

Hi @Andy3 ,

if you need to do it, you can use Data to Weights for it. Attached is an example.

BR,

Martin

<?xml version="1.0" encoding="UTF-8"?><process version="9.6.000">
  <context>
    <input/>
    <output/>
    <macros/>
  </context>
  <operator activated="true" class="process" compatibility="9.6.000" 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="9.6.000" expanded="true" height="68" name="Retrieve Sonar" width="90" x="45" y="34">
        <parameter key="repository_entry" value="//Samples/data/Sonar"/>
      </operator>
      <operator activated="true" class="select_attributes" compatibility="9.6.000" expanded="true" height="82" name="Select Attributes" width="90" x="179" y="34">
        <parameter key="attribute_filter_type" value="single"/>
        <parameter key="attribute" value="attribute_1"/>
        <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="false"/>
      </operator>
      <operator activated="true" class="data_to_weights" compatibility="9.6.000" expanded="true" height="82" name="Data to Weights" width="90" x="313" y="34">
        <parameter key="normalize_weights" value="false"/>
        <parameter key="sort_weights" value="true"/>
        <parameter key="sort_direction" value="ascending"/>
      </operator>
      <operator activated="true" class="retrieve" compatibility="9.6.000" expanded="true" height="68" name="Retrieve Sonar (2)" width="90" x="45" y="238">
        <parameter key="repository_entry" value="//Samples/data/Sonar"/>
      </operator>
      <operator activated="true" class="select_by_weights" compatibility="9.6.000" expanded="true" height="103" name="Select by Weights" width="90" x="514" y="136">
        <parameter key="weight_relation" value="greater equals"/>
        <parameter key="weight" value="1.0"/>
        <parameter key="k" value="10"/>
        <parameter key="p" value="0.5"/>
        <parameter key="deselect_unknown" value="true"/>
        <parameter key="use_absolute_weights" value="true"/>
      </operator>
      <connect from_op="Retrieve Sonar" from_port="output" to_op="Select Attributes" to_port="example set input"/>
      <connect from_op="Select Attributes" from_port="example set output" to_op="Data to Weights" to_port="example set"/>
      <connect from_op="Data to Weights" from_port="weights" to_op="Select by Weights" to_port="weights"/>
      <connect from_op="Retrieve Sonar (2)" from_port="output" to_op="Select by Weights" to_port="example set input"/>
      <connect from_op="Select by Weights" from_port="example set output" to_port="result 1"/>
      <portSpacing port="source_input 1" spacing="0"/>
      <portSpacing port="sink_result 1" spacing="0"/>
      <portSpacing port="sink_result 2" spacing="0"/>
    </process>
  </operator>
</process>

Andy3

Yeah, fair enough though I was hoping the where an operator(s) like this so I could have consistency through the various data sets (and in my mind ). I leave it there.

Thanks for the help.