"[SOLVED] Logging Confidences in X-Validation"

SkyfallerSkyfaller Member Posts: 2 Contributor I
edited June 10 in Help
Hi Guys,

okay i have a little problem which i cant seem to solve on my own.
The thing is:
I have a Cross-Validation. As usual in the Training part is the "classifier" (SVM with "calculate confidence") and in the Test part the "apply model" and "performance" Operator.

Now I want to write the confidences to a file. But the outputs of the Cross-Validation doesn't give me the confidences back.

Now i'm trying to write the confidences in the Testing part to a file(write-csv), this seems to work, but unfortunately it overwrites the file in each Step. Which means i only get the last 1/10th of the Data in the File.

In short: Is there any way to write the Output (labelled date) of the "apply model" operator to a file for every iteration of the cross-validation?
If possible to a single file.

Thanks,
Nic

Answers

  • haddockhaddock Member Posts: 849  Guru
    Hi there,

    Is this what you had in mind?
    <?xml version="1.0" encoding="UTF-8" standalone="no"?>
    <process version="5.1.013">
      <context>
        <input/>
        <output/>
        <macros/>
      </context>
      <operator activated="true" class="process" compatibility="5.1.013" expanded="true" name="Root">
        <process expanded="true" height="584" width="915">
          <operator activated="true" class="retrieve" compatibility="5.1.013" expanded="true" height="60" name="Retrieve" width="90" x="45" y="30">
            <parameter key="repository_entry" value="../../data/Labor-Negotiations"/>
          </operator>
          <operator activated="true" class="replace_missing_values" compatibility="5.1.013" expanded="true" height="94" name="MissingValueReplenishment" width="90" x="180" y="30">
            <list key="columns"/>
          </operator>
          <operator activated="true" class="x_validation" compatibility="5.1.013" expanded="true" height="112" name="XValidation" width="90" x="315" y="30">
            <parameter key="number_of_validations" value="5"/>
            <process expanded="true" height="347" width="385">
              <operator activated="true" class="k_nn" compatibility="5.1.013" expanded="true" height="76" name="NearestNeighbors" width="90" x="152" y="30">
                <parameter key="k" value="3"/>
              </operator>
              <connect from_port="training" to_op="NearestNeighbors" to_port="training set"/>
              <connect from_op="NearestNeighbors" 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" height="347" width="413">
              <operator activated="true" class="apply_model" compatibility="5.1.013" expanded="true" height="76" name="ModelApplier" width="90" x="45" y="30">
                <list key="application_parameters"/>
              </operator>
              <operator activated="true" class="write_special" compatibility="5.1.013" expanded="true" height="60" name="Write Special Format" width="90" x="147" y="166">
                <parameter key="example_set_file" value="C:\Documents and Settings\Administrator.KNOWLEDG-P6715Y\My Documents\out.dat"/>
                <parameter key="special_format" value="$d"/>
              </operator>
              <operator activated="true" class="performance_classification" compatibility="5.1.013" expanded="true" height="76" name="ClassificationPerformance" width="90" x="246" y="30">
                <parameter key="accuracy" value="false"/>
                <parameter key="classification_error" value="true"/>
                <list key="class_weights"/>
              </operator>
              <connect from_port="model" to_op="ModelApplier" to_port="model"/>
              <connect from_port="test set" to_op="ModelApplier" to_port="unlabelled data"/>
              <connect from_op="ModelApplier" from_port="labelled data" to_op="Write Special Format" to_port="input"/>
              <connect from_op="Write Special Format" from_port="through" to_op="ClassificationPerformance" to_port="labelled data"/>
              <connect from_op="ClassificationPerformance" 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>
          <connect from_op="Retrieve" from_port="output" to_op="MissingValueReplenishment" to_port="example set input"/>
          <connect from_op="MissingValueReplenishment" from_port="example set output" to_op="XValidation" to_port="training"/>
          <connect from_op="XValidation" from_port="averagable 1" 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>
    Hope so!
  • SkyfallerSkyfaller Member Posts: 2 Contributor I
    Hi Haddock,

    first of all a BIG Thanks :)

    Yeah thats exactly what i had in mind.
    Seems to work perfectly :)

    Thank you very very much!

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