Logistic Regression Wald test

Mori111Mori111 Member, University Professor Posts: 9 University Professor
edited March 2020 in Help
I cannot find which performance operator gives me the wald test for logistic regression 
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Jasmine_

Answers

  • yyhuangyyhuang Administrator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 364 RM Data Scientist
    Hi @Mori111,

    Do you want to compute p-value for the significance of the factors in Logistic Regression? Just check the box and enable it in GLM or Log Regression operator.


    <?xml version="1.0" encoding="UTF-8"?><process version="9.6.000">
      <context>
        <input/>
        <output/>
        <macros/>
      </context>
      <operator activated="true" class="process" compatibility="9.4.000" expanded="true" name="Process" origin="GENERATED_TUTORIAL">
        <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 Deals" origin="GENERATED_TUTORIAL" width="90" x="45" y="34">
            <parameter key="repository_entry" value="//Samples/data/Deals"/>
          </operator>
          <operator activated="true" class="h2o:logistic_regression" compatibility="9.3.001" expanded="true" height="124" name="Logistic Regression" origin="GENERATED_TUTORIAL" width="90" x="179" y="34">
            <parameter key="solver" value="AUTO"/>
            <parameter key="reproducible" value="true"/>
            <parameter key="maximum_number_of_threads" value="4"/>
            <parameter key="use_regularization" value="false"/>
            <parameter key="lambda_search" value="false"/>
            <parameter key="number_of_lambdas" value="0"/>
            <parameter key="lambda_min_ratio" value="0.0"/>
            <parameter key="early_stopping" value="true"/>
            <parameter key="stopping_rounds" value="3"/>
            <parameter key="stopping_tolerance" value="0.001"/>
            <parameter key="standardize" value="true"/>
            <parameter key="non-negative_coefficients" value="false"/>
            <parameter key="add_intercept" value="true"/>
            <parameter key="compute_p-values" value="true"/>
            <parameter key="remove_collinear_columns" value="true"/>
            <parameter key="missing_values_handling" value="MeanImputation"/>
            <parameter key="max_iterations" value="0"/>
            <parameter key="max_runtime_seconds" value="0"/>
          </operator>
          <operator activated="true" class="retrieve" compatibility="9.6.000" expanded="true" height="68" name="Retrieve Sonar" width="90" x="45" y="238">
            <parameter key="repository_entry" value="//Samples/data/Sonar"/>
          </operator>
          <operator activated="true" class="h2o:logistic_regression" compatibility="9.3.001" expanded="true" height="124" name="Logistic Regression (2)" origin="GENERATED_TUTORIAL" width="90" x="179" y="238">
            <parameter key="solver" value="AUTO"/>
            <parameter key="reproducible" value="true"/>
            <parameter key="maximum_number_of_threads" value="4"/>
            <parameter key="use_regularization" value="false"/>
            <parameter key="lambda_search" value="false"/>
            <parameter key="number_of_lambdas" value="0"/>
            <parameter key="lambda_min_ratio" value="0.0"/>
            <parameter key="early_stopping" value="true"/>
            <parameter key="stopping_rounds" value="3"/>
            <parameter key="stopping_tolerance" value="0.001"/>
            <parameter key="standardize" value="true"/>
            <parameter key="non-negative_coefficients" value="false"/>
            <parameter key="add_intercept" value="true"/>
            <parameter key="compute_p-values" value="true"/>
            <parameter key="remove_collinear_columns" value="true"/>
            <parameter key="missing_values_handling" value="MeanImputation"/>
            <parameter key="max_iterations" value="0"/>
            <parameter key="max_runtime_seconds" value="0"/>
          </operator>
          <connect from_op="Retrieve Deals" from_port="output" to_op="Logistic Regression" to_port="training set"/>
          <connect from_op="Logistic Regression" from_port="model" to_port="result 1"/>
          <connect from_op="Retrieve Sonar" from_port="output" to_op="Logistic Regression (2)" to_port="training set"/>
          <connect from_op="Logistic Regression (2)" from_port="model" 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>
    




    Cheers,
    YY
    varunm1Mori111sgenzerJasmine_
  • Mori111Mori111 Member, University Professor Posts: 9 University Professor
    Thanks so much!
    Jasmine_
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