Normalization (training) with clustering (group model) does not work as expected

amitd

Using a Normalization operator alongside k-Means operator to create a group model within a Cross-Validation or Split-Validation does not work because the Performance (Cluster Distance Performance) operator expects a CentroidClusterModel but instead received a GroupedModel. It seems that the Performance (Cluster Distance Performance) operator needs to be updated to accommodate a grouped model.
A simple example using the Iris dataset in the RapidMiner Samples directory is attached showing the issue.

YYH

Dear Prof @amitdeokar

Thanks for sharing the process of cross validated K-means. The normalize pre-processing model is grouped with clustering model in the training phase. But the clustering performance operator can only take a cluster model as a input, not a grouped model.

How about this ungroup and select added here in the testing phase?

<?xml version="1.0" encoding="UTF-8"?><process version="9.3.001">
  <context>
    <input/>
    <output/>
    <macros/>
  </context>
  <operator activated="true" class="process" compatibility="9.3.001" expanded="true" name="Process">
    <parameter key="logverbosity" value="init"/>
    <parameter key="random_seed" value="2001"/>
    <parameter key="send_mail" value="never"/>
    <parameter key="notification_email" value=""/>
    <parameter key="process_duration_for_mail" value="30"/>
    <parameter key="encoding" value="SYSTEM"/>
    <process expanded="true">
      <operator activated="true" class="retrieve" compatibility="9.3.001" expanded="true" height="68" name="Retrieve Iris (2)" width="90" x="45" y="34">
        <parameter key="repository_entry" value="//Samples/data/Iris"/>
      </operator>
      <operator activated="true" class="concurrency:cross_validation" compatibility="9.3.001" expanded="true" height="145" name="Cross Validation" width="90" x="313" y="34">
        <parameter key="split_on_batch_attribute" value="false"/>
        <parameter key="leave_one_out" value="false"/>
        <parameter key="number_of_folds" value="10"/>
        <parameter key="sampling_type" value="automatic"/>
        <parameter key="use_local_random_seed" value="false"/>
        <parameter key="local_random_seed" value="1992"/>
        <parameter key="enable_parallel_execution" value="true"/>
        <process expanded="true">
          <operator activated="true" class="normalize" compatibility="9.3.001" expanded="true" height="103" name="Normalize" width="90" x="45" y="34">
            <parameter key="return_preprocessing_model" value="false"/>
            <parameter key="create_view" value="false"/>
            <parameter key="attribute_filter_type" value="all"/>
            <parameter key="attribute" value=""/>
            <parameter key="attributes" value=""/>
            <parameter key="use_except_expression" value="false"/>
            <parameter key="value_type" value="numeric"/>
            <parameter key="use_value_type_exception" value="false"/>
            <parameter key="except_value_type" value="real"/>
            <parameter key="block_type" value="value_series"/>
            <parameter key="use_block_type_exception" value="false"/>
            <parameter key="except_block_type" value="value_series_end"/>
            <parameter key="invert_selection" value="false"/>
            <parameter key="include_special_attributes" value="false"/>
            <parameter key="method" value="Z-transformation"/>
            <parameter key="min" value="0.0"/>
            <parameter key="max" value="1.0"/>
            <parameter key="allow_negative_values" value="false"/>
          </operator>
          <operator activated="true" class="concurrency:k_means" compatibility="9.3.001" expanded="true" height="82" name="Clustering" width="90" x="313" y="34">
            <parameter key="add_cluster_attribute" value="true"/>
            <parameter key="add_as_label" value="false"/>
            <parameter key="remove_unlabeled" value="false"/>
            <parameter key="k" value="5"/>
            <parameter key="max_runs" value="10"/>
            <parameter key="determine_good_start_values" value="true"/>
            <parameter key="measure_types" value="BregmanDivergences"/>
            <parameter key="mixed_measure" value="MixedEuclideanDistance"/>
            <parameter key="nominal_measure" value="NominalDistance"/>
            <parameter key="numerical_measure" value="EuclideanDistance"/>
            <parameter key="divergence" value="SquaredEuclideanDistance"/>
            <parameter key="kernel_type" value="radial"/>
            <parameter key="kernel_gamma" value="1.0"/>
            <parameter key="kernel_sigma1" value="1.0"/>
            <parameter key="kernel_sigma2" value="0.0"/>
            <parameter key="kernel_sigma3" value="2.0"/>
            <parameter key="kernel_degree" value="3.0"/>
            <parameter key="kernel_shift" value="1.0"/>
            <parameter key="kernel_a" value="1.0"/>
            <parameter key="kernel_b" value="0.0"/>
            <parameter key="max_optimization_steps" value="100"/>
            <parameter key="use_local_random_seed" value="false"/>
            <parameter key="local_random_seed" value="1992"/>
          </operator>
          <operator activated="true" class="group_models" compatibility="9.3.001" expanded="true" height="103" name="Group Models" width="90" x="380" y="187"/>
          <connect from_port="training set" to_op="Normalize" to_port="example set input"/>
          <connect from_op="Normalize" from_port="example set output" to_op="Clustering" to_port="example set"/>
          <connect from_op="Normalize" from_port="preprocessing model" to_op="Group Models" to_port="models in 1"/>
          <connect from_op="Clustering" from_port="cluster model" to_op="Group Models" to_port="models in 2"/>
          <connect from_op="Group Models" from_port="model out" to_port="model"/>
          <portSpacing port="source_training set" spacing="0"/>
          <portSpacing port="sink_model" spacing="0"/>
          <portSpacing port="sink_through 1" spacing="0"/>
        </process>
        <process expanded="true">
          <operator activated="true" class="apply_model" compatibility="9.3.001" expanded="true" height="82" name="Apply Model" width="90" x="45" y="34">
            <list key="application_parameters"/>
            <parameter key="create_view" value="false"/>
          </operator>
          <operator activated="true" class="ungroup_models" compatibility="9.3.001" expanded="true" height="68" name="Ungroup Models" width="90" x="179" y="85"/>
          <operator activated="true" class="select" compatibility="9.3.001" expanded="true" height="68" name="Select" width="90" x="313" y="85">
            <parameter key="index" value="2"/>
            <parameter key="unfold" value="false"/>
          </operator>
          <operator activated="true" class="cluster_distance_performance" compatibility="9.3.001" expanded="true" height="103" name="Performance" width="90" x="447" y="34">
            <parameter key="main_criterion" value="Avg. within centroid distance"/>
            <parameter key="main_criterion_only" value="false"/>
            <parameter key="normalize" value="false"/>
            <parameter key="maximize" value="false"/>
          </operator>
          <connect from_port="model" to_op="Apply Model" to_port="model"/>
          <connect from_port="test set" to_op="Apply Model" to_port="unlabelled data"/>
          <connect from_op="Apply Model" from_port="labelled data" to_op="Performance" to_port="example set"/>
          <connect from_op="Apply Model" from_port="model" to_op="Ungroup Models" to_port="grouped model"/>
          <connect from_op="Ungroup Models" from_port="models" to_op="Select" to_port="collection"/>
          <connect from_op="Select" from_port="selected" to_op="Performance" to_port="cluster model"/>
          <connect from_op="Performance" from_port="performance" to_port="performance 1"/>
          <connect from_op="Performance" from_port="example set" to_port="test set results"/>
          <portSpacing port="source_model" spacing="0"/>
          <portSpacing port="source_test set" spacing="0"/>
          <portSpacing port="source_through 1" spacing="0"/>
          <portSpacing port="sink_test set results" spacing="0"/>
          <portSpacing port="sink_performance 1" spacing="0"/>
          <portSpacing port="sink_performance 2" spacing="0"/>
        </process>
      </operator>
      <connect from_op="Retrieve Iris (2)" from_port="output" to_op="Cross Validation" to_port="example set"/>
      <connect from_op="Cross Validation" from_port="model" to_port="result 1"/>
      <connect from_op="Cross Validation" from_port="performance 1" to_port="result 2"/>
      <portSpacing port="source_input 1" spacing="0"/>
      <portSpacing port="sink_result 1" spacing="21"/>
      <portSpacing port="sink_result 2" spacing="0"/>
      <portSpacing port="sink_result 3" spacing="252"/>
    </process>
  </operator>
</process>

Best,

YY