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Random Forest

User: "Liverpool_Reds"
Liverpool_Reds
New Altair Community Member
Updated by Jocelyn

Could anyone please explain how Rapidminer implementation of Random Forest operator handles missing values in attributes.

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    User: "SGolbert"
    SGolbert
    New Altair Community Member

    Hi,

     

    Both in Random Forest and Decision Trees, missing values are treated like a separate data value, both for numerical and nominal attributes. You can check it out yourself in the following process:

     

    <?xml version="1.0" encoding="UTF-8"?><process version="9.0.000">
      <context>
        <input/>
        <output/>
        <macros/>
      </context>
      <operator activated="true" class="process" compatibility="9.0.000" expanded="true" name="Process">
        <process expanded="true">
          <operator activated="true" class="retrieve" compatibility="9.0.000" expanded="true" height="68" name="Retrieve Titanic Training" width="90" x="112" y="34">
            <parameter key="repository_entry" value="//Samples/data/Titanic Training"/>
          </operator>
          <operator activated="true" class="declare_missing_value" compatibility="9.0.000" expanded="true" height="82" name="Declare Missing Value" width="90" x="246" y="34">
            <parameter key="attribute_filter_type" value="single"/>
            <parameter key="attribute" value="Sex"/>
            <parameter key="mode" value="nominal"/>
            <parameter key="nominal_value" value="Female"/>
          </operator>
          <operator activated="true" class="declare_missing_value" compatibility="9.0.000" expanded="true" height="82" name="Declare Missing Value (2)" width="90" x="447" y="34">
            <parameter key="attribute_filter_type" value="single"/>
            <parameter key="attribute" value="Age"/>
            <parameter key="mode" value="expression"/>
            <parameter key="nominal_value" value="Female"/>
            <parameter key="expression_value" value="Age&gt;40"/>
          </operator>
          <operator activated="true" class="concurrency:parallel_random_forest" compatibility="9.0.000" expanded="true" height="103" name="Random Forest" width="90" x="648" y="34"/>
          <connect from_op="Retrieve Titanic Training" from_port="output" to_op="Declare Missing Value" to_port="example set input"/>
          <connect from_op="Declare Missing Value" from_port="example set output" to_op="Declare Missing Value (2)" to_port="example set input"/>
          <connect from_op="Declare Missing Value (2)" from_port="example set output" to_op="Random Forest" to_port="training set"/>
          <connect from_op="Random Forest" from_port="model" 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>

    Note that for numerical attributes it results in a 3-way split.

     

    With Decision Tree models, inputing missing values doesn't improve the model, unless you have a very precise way to do it.

     

    Regards,

    Sebastian

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