Why Converter "Logistic Regression to ExampleSet" won't work?

TNT
TNT New Altair Community Member
edited November 2024 in Community Q&A
I thought this was a problem of my model, but it doesn't work in the Tutorial either. Error message is "Wrong connection. Your connection is producing the wrong type of data. Try changing the starting point of the connection."

<?xml version="1.0" encoding="UTF-8"?><process version="9.9.000">
  <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="9.9.000" 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="7.2.000" 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="false"/>
        <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="converters:h2o_logreg_2_example_set" compatibility="0.9.000" expanded="true" height="82" name="Logistic Regression to ExampleSet" origin="GENERATED_TUTORIAL" width="90" x="380" y="34"/>
      <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_op="Logistic Regression to ExampleSet" to_port="mod"/>
      <connect from_op="Logistic Regression to ExampleSet" from_port="exa" 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"/>


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Best Answer

  • MartinLiebig
    MartinLiebig
    Altair Employee
    Answer ✓
    Hi @TNT ,
    i fixed it in our development version. Its being reviewed and be fixed in the next version of Converters.

    Best,
    Martin

Answers

  • lionelderkrikor
    lionelderkrikor New Altair Community Member
    Hi @TNT,

    A workaround is to use Linear Regression Model to ExampleSet operator instead 
    Logistic Regression to ExampleSet operator...

    Hope this helps,

    Regards,

    Lionel
  • MartinLiebig
    MartinLiebig
    Altair Employee
    Hi,

    sorry, that's a straight up bug. We will look into this.

    Best,
    Martin
  • MartinLiebig
    MartinLiebig
    Altair Employee
    Answer ✓
    Hi @TNT ,
    i fixed it in our development version. Its being reviewed and be fixed in the next version of Converters.

    Best,
    Martin
  • TNT
    TNT New Altair Community Member
    Thanks both for the timely response. The workaround does fundamentally work although I do need to fiddle with some following attribute expressions and look forward to the corrected version. 

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