[SOLVED] No R Squared for Linear Regression?
diannej6
New Altair Community Member
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.
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.
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Answers
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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>0 -
Thank you so much for your help!0