[SOLVED] No R Squared for Linear Regression?

diannej6

I have been using Excel's Regression tool, but switch to RapidMiner when I have too many independent variables to use Excel.
I am accumstomed to review the p-Value for each indepedent variable and the R Square(d) for the dataset.
I do not see an R Square(d) result within RapidMiner's results, in the Table View or the Text View.
Is there any way for me to get this information?

Thank you.

earmijo

In RapidMiner you have to ask for it explicitly. In the process below I ask RM for the performance metrics available for a prediction problem. R^2 is called Squared Correlation.

<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<process version="5.3.005">
  <context>
    <input/>
    <output/>
    <macros/>
  </context>
  <operator activated="true" class="process" compatibility="5.3.005" expanded="true" name="Root">
    <description>This learner creates a linear regression model allowing numerical predictions for the loaded data set.</description>
    <process expanded="true">
      <operator activated="true" class="retrieve" compatibility="5.3.005" expanded="true" height="60" name="Retrieve" width="90" x="45" y="30">
        <parameter key="repository_entry" value="../../data/Polynomial"/>
      </operator>
      <operator activated="true" class="linear_regression" compatibility="5.3.005" expanded="true" height="94" name="LinearRegression" width="90" x="179" y="75"/>
      <operator activated="true" class="apply_model" compatibility="5.3.005" expanded="true" height="76" name="Apply Model" width="90" x="380" y="75">
        <list key="application_parameters"/>
      </operator>
      <operator activated="true" class="performance_regression" compatibility="5.3.005" expanded="true" height="76" name="Performance" width="90" x="514" y="30">
        <parameter key="absolute_error" value="true"/>
        <parameter key="relative_error" value="true"/>
        <parameter key="relative_error_lenient" value="true"/>
        <parameter key="relative_error_strict" value="true"/>
        <parameter key="normalized_absolute_error" value="true"/>
        <parameter key="root_relative_squared_error" value="true"/>
        <parameter key="squared_error" value="true"/>
        <parameter key="correlation" value="true"/>
        <parameter key="squared_correlation" value="true"/>
        <parameter key="prediction_average" value="true"/>
        <parameter key="spearman_rho" value="true"/>
        <parameter key="kendall_tau" value="true"/>
      </operator>
      <connect from_op="Retrieve" from_port="output" to_op="LinearRegression" to_port="training set"/>
      <connect from_op="LinearRegression" from_port="model" to_op="Apply Model" to_port="model"/>
      <connect from_op="LinearRegression" from_port="exampleSet" to_op="Apply Model" to_port="unlabelled data"/>
      <connect from_op="Apply Model" from_port="labelled data" to_op="Performance" to_port="labelled data"/>
      <connect from_op="Performance" from_port="performance" 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>