Parameters of the node Create Association Rules

kaiserkaiser Member Posts: 1 Contributor I
What meaning have the parameters gain theta and laplace k of the node Create Association Rules?

Answers

  • haddockhaddock Member Posts: 849  Guru
    Wotcha!

    As I understand it they are statistics that you could use to sift your rules. One of the the problems with Association Rule Mining is that you may end up with more rules than examples ( as an example could support more than one frequent item set ), so sifting through the sh.. becomes important.

    You can see all the statistics of your rule set by converting them to examples. You may find it useful to cannibalise this process, hope so!
    <?xml version="1.0" encoding="UTF-8" standalone="no"?>
    <process version="5.2.003">
      <context>
        <input/>
        <output/>
        <macros/>
      </context>
      <operator activated="true" class="process" compatibility="5.0.000" expanded="true" name="Root">
        <parameter key="logverbosity" value="warning"/>
        <process expanded="true" height="217" width="745">
          <operator activated="true" class="retrieve" compatibility="5.0.000" expanded="true" height="60" name="Retrieve" width="90" x="45" y="30">
            <parameter key="repository_entry" value="//Samples/data/Iris"/>
          </operator>
          <operator activated="true" class="subprocess" compatibility="5.0.000" expanded="true" height="76" name="Preprocessing" width="90" x="180" y="30">
            <process expanded="true">
              <operator activated="true" class="discretize_by_frequency" compatibility="5.0.000" expanded="true" name="FrequencyDiscretization">
                <parameter key="number_of_bins" value="5"/>
              </operator>
              <operator activated="true" class="nominal_to_binominal" compatibility="5.0.000" expanded="true" name="Nominal2Binominal">
                <parameter key="transform_binominal" value="true"/>
              </operator>
              <connect from_port="in 1" to_op="FrequencyDiscretization" to_port="example set input"/>
              <connect from_op="FrequencyDiscretization" from_port="example set output" to_op="Nominal2Binominal" to_port="example set input"/>
              <connect from_op="Nominal2Binominal" from_port="example set output" to_port="out 1"/>
              <portSpacing port="source_in 1" spacing="0"/>
              <portSpacing port="source_in 2" spacing="0"/>
              <portSpacing port="sink_out 1" spacing="0"/>
              <portSpacing port="sink_out 2" spacing="0"/>
            </process>
          </operator>
          <operator activated="true" class="fp_growth" compatibility="5.0.000" expanded="true" height="76" name="FPGrowth" width="90" x="313" y="30">
            <parameter key="find_min_number_of_itemsets" value="false"/>
            <parameter key="min_support" value="0.1"/>
          </operator>
          <operator activated="true" class="create_association_rules" compatibility="5.0.000" expanded="true" height="76" name="AssociationRuleGenerator" width="90" x="313" y="165">
            <parameter key="min_confidence" value="0.7"/>
          </operator>
          <operator activated="true" class="execute_script" compatibility="5.0.000" expanded="true" height="76" name="Execute Script" width="90" x="581" y="75">
            <parameter key="script" value="import com.rapidminer.tools.Ontology;&#13;&#13;&#10;import com.rapidminer.operator.learner.associations.*;&#13;&#13;&#10;&#13;&#10;AssociationRules rules = input[0];&#13;&#13;&#10;&#10;&#13;// construct attribute set&#13;&#10;Attribute[] attributes= new Attribute[11];&#10;attributes[0] = AttributeFactory.createAttribute(&quot;Premise&quot;, Ontology.STRING);&#13;&#13;&#10;attributes[1] = AttributeFactory.createAttribute(&quot;Premise Items&quot;, Ontology.INTEGER);&#10;attributes[2] = AttributeFactory.createAttribute(&quot;Conclusion&quot;, Ontology.STRING);&#13;&#10;attributes[3] = AttributeFactory.createAttribute(&quot;Conclusion Items&quot;, Ontology.INTEGER);&#13;&#10;attributes[4] = AttributeFactory.createAttribute(&quot;Confidence&quot;, Ontology.REAL);&#13;&#10;attributes[5] = AttributeFactory.createAttribute(&quot;Conviction&quot;, Ontology.REAL);&#13;&#10;attributes[6] = AttributeFactory.createAttribute(&quot;Gain&quot;, Ontology.REAL);&#13;&#10;attributes[7] = AttributeFactory.createAttribute(&quot;Laplace&quot;, Ontology.REAL);&#13;&#13;&#10;attributes[8] = AttributeFactory.createAttribute(&quot;Lift&quot;, Ontology.REAL);&#13;&#10;attributes[9] = AttributeFactory.createAttribute(&quot;Ps&quot;, Ontology.REAL);&#10;&#13;&#13;attributes[10] = AttributeFactory.createAttribute(&quot;Total Support&quot;, Ontology.REAL);&#10;&#13;&#13;&#13;&#10;MemoryExampleTable table = new MemoryExampleTable(attributes);&#10;DataRowFactory ROW_FACTORY = new DataRowFactory(0);&#13;&#10;&#13;String[] strings= new String[11];&#13;&#10;&#10;for (AssociationRule rule : rules) {&#10;&#9;&#9;// construct example data&#10;        strings[0]=rule.toPremiseString();&#13;&#10;        strings[1]=rule.premise.size().toString();&#13;&#10;        strings[2]=rule.toConclusionString();&#13;&#10;        strings[3]=rule.conclusion.size().toString();&#13;&#10;        strings[4]=rule.getConfidence().toString();&#13;&#10;        strings[5]=rule.getConviction().toString();&#13;&#10;        strings[6]=rule.getGain().toString();&#13;&#10;        strings[7]=rule.getLaplace().toString();&#13;&#10;        strings[8]=rule.getLift().toString();&#13;&#10;&#13;        strings[9]=rule.getPs().toString();&#13;&#10;        strings[10]=rule.getTotalSupport().toString();&#13;&#13;&#10;        // make and add row&#13;&#10;        DataRow row = ROW_FACTORY.create(strings, attributes); &#13;&#10;        table.addDataRow(row);&#9;&#10;&#9;&#9;}&#10;&#13;&#10;ExampleSet exampleSet = table.createExampleSet();&#10;return exampleSet;&#10;"/>
          </operator>
          <connect from_op="Retrieve" from_port="output" to_op="Preprocessing" to_port="in 1"/>
          <connect from_op="Preprocessing" from_port="out 1" to_op="FPGrowth" to_port="example set"/>
          <connect from_op="FPGrowth" from_port="frequent sets" to_op="AssociationRuleGenerator" to_port="item sets"/>
          <connect from_op="AssociationRuleGenerator" from_port="rules" to_op="Execute Script" to_port="input 1"/>
          <connect from_op="Execute Script" from_port="output 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>
    Good luck!
Sign In or Register to comment.