"[Solved] Set Macro dynamically based on Dataset"

Hi ,

I am doing a down sampling by use of clustering , it's an imbalanced dataset which the number of example with 'f' label is about 6 times more than the number of examples with 't' label,

I want to set the K in clustering module equals to number of 't' examples in the dataset ,

How can I do that ?

Thanks

<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<process version="5.2.008">
  <context>
    <input/>
    <output/>
    <macros/>
  </context>
  <operator activated="true" class="process" compatibility="5.2.008" expanded="true" name="Process">
    <process expanded="true" height="539" width="2225">
      <operator activated="true" class="retrieve" compatibility="5.2.008" expanded="true" height="60" name="Retrieve" width="90" x="45" y="75">
        <parameter key="repository_entry" value="//NewLocalRepository/temp_5000sampled_MI4"/>
      </operator>
      <operator activated="true" class="sample_stratified" compatibility="5.2.008" expanded="true" height="76" name="Sample (Stratified)" width="90" x="112" y="210">
        <parameter key="sample" value="relative"/>
      </operator>
      <operator activated="true" class="nominal_to_numerical" compatibility="5.2.008" expanded="true" height="94" name="Nominal to Numerical" width="90" x="246" y="75">
        <parameter key="attribute_filter_type" value="single"/>
        <parameter key="attribute" value="sex"/>
        <list key="comparison_groups"/>
      </operator>
      <operator activated="true" class="normalize" compatibility="5.2.008" expanded="true" height="94" name="Normalize" width="90" x="380" y="75"/>
      <operator activated="false" class="select_attributes" compatibility="5.2.008" expanded="true" height="76" name="Select Attributes" width="90" x="179" y="345">
        <parameter key="attribute_filter_type" value="single"/>
        <parameter key="attribute" value="event"/>
        <parameter key="invert_selection" value="true"/>
      </operator>
      <operator activated="true" class="multiply" compatibility="5.2.008" expanded="true" height="94" name="Multiply" width="90" x="581" y="75"/>
      <operator activated="true" class="filter_examples" compatibility="5.2.008" expanded="true" height="76" name="Filter Examples (2)" width="90" x="782" y="255">
        <parameter key="condition_class" value="attribute_value_filter"/>
        <parameter key="parameter_string" value="event=t"/>
      </operator>
      <operator activated="true" class="filter_examples" compatibility="5.2.008" expanded="true" height="76" name="Filter Examples" width="90" x="782" y="30">
        <parameter key="condition_class" value="attribute_value_filter"/>
        <parameter key="parameter_string" value="event=f"/>
      </operator>
      <operator activated="true" class="multiply" compatibility="5.2.008" expanded="true" height="94" name="Multiply (2)" width="90" x="916" y="30"/>
      <operator activated="true" class="k_means" compatibility="5.2.008" expanded="true" height="76" name="Clustering" width="90" x="1117" y="30">
        <parameter key="k" value="4"/>
        <parameter key="max_runs" value="100"/>
        <parameter key="measure_types" value="MixedMeasures"/>
      </operator>
      <operator activated="true" class="apply_model" compatibility="5.2.008" expanded="true" height="76" name="Apply Model" width="90" x="1117" y="165">
        <list key="application_parameters"/>
      </operator>
      <operator activated="true" class="remove_duplicates" compatibility="5.2.008" expanded="true" height="76" name="Remove Duplicates" width="90" x="1452" y="165">
        <parameter key="attribute_filter_type" value="single"/>
        <parameter key="attribute" value="cluster"/>
        <parameter key="include_special_attributes" value="true"/>
      </operator>
      <operator activated="true" class="union" compatibility="5.2.008" expanded="true" height="76" name="Union" width="90" x="1720" y="210"/>
      <operator activated="true" class="select_attributes" compatibility="5.2.008" expanded="true" height="76" name="Select Attributes (3)" width="90" x="1921" y="210">
        <parameter key="attribute_filter_type" value="single"/>
        <parameter key="attribute" value="cluster"/>
        <parameter key="invert_selection" value="true"/>
        <parameter key="include_special_attributes" value="true"/>
      </operator>
      <operator activated="true" class="shuffle" compatibility="5.2.008" expanded="true" height="76" name="Shuffle" width="90" x="2055" y="210"/>
      <connect from_op="Retrieve" from_port="output" to_op="Sample (Stratified)" to_port="example set input"/>
      <connect from_op="Sample (Stratified)" from_port="example set output" to_op="Nominal to Numerical" to_port="example set input"/>
      <connect from_op="Nominal to Numerical" from_port="example set output" to_op="Normalize" to_port="example set input"/>
      <connect from_op="Normalize" from_port="example set output" to_op="Multiply" to_port="input"/>
      <connect from_op="Multiply" from_port="output 1" to_op="Filter Examples" to_port="example set input"/>
      <connect from_op="Multiply" from_port="output 2" to_op="Filter Examples (2)" to_port="example set input"/>
      <connect from_op="Filter Examples (2)" from_port="example set output" to_op="Union" to_port="example set 2"/>
      <connect from_op="Filter Examples" from_port="example set output" to_op="Multiply (2)" to_port="input"/>
      <connect from_op="Multiply (2)" from_port="output 1" to_op="Clustering" to_port="example set"/>
      <connect from_op="Multiply (2)" from_port="output 2" to_op="Apply Model" to_port="unlabelled data"/>
      <connect from_op="Clustering" from_port="cluster model" to_op="Apply Model" to_port="model"/>
      <connect from_op="Apply Model" from_port="labelled data" to_op="Remove Duplicates" to_port="example set input"/>
      <connect from_op="Remove Duplicates" from_port="example set output" to_op="Union" to_port="example set 1"/>
      <connect from_op="Union" from_port="union" to_op="Select Attributes (3)" to_port="example set input"/>
      <connect from_op="Select Attributes (3)" from_port="example set output" to_op="Shuffle" to_port="example set input"/>
      <connect from_op="Shuffle" from_port="example set output" 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>