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"Cluster Result"

mskhmskh Member Posts: 13 Learner I
edited May 2019 in Help
Hi everyone,
I use DBSCAN to cluster my dataset. I know how to label the anomaly cluster (e.g. cluster_2) as false and other as true (by using if statement and set Role). If my dataset changes, the anomaly cluster will change and i can not specify cluster in if statement. how can i determine which cluster has the lowest number of instances and use the cluster in if statement.
Thanks
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Answers

  • lionelderkrikorlionelderkrikor RapidMiner Certified Analyst, Member Posts: 1,195 Unicorn
    Hi @mina_s_kh,

    Here a process to count the number of elements in the cluster(s). The results are sorted, so that the first element of the list is the cluster with the lowest number of elements : 
    <?xml version="1.0" encoding="UTF-8"?><process version="9.2.000">
  <context>
    <input/>
    <output/>
    <macros/>
  </context>
  <operator activated="true" class="process" compatibility="9.2.000" expanded="true" name="Process" origin="GENERATED_TUTORIAL">
    <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="9.2.000" expanded="true" height="68" name="Ripley-Set" origin="GENERATED_TUTORIAL" width="90" x="179" y="34">
        <parameter key="repository_entry" value="//Samples/data/Ripley-Set"/>
      </operator>
      <operator activated="true" breakpoints="after" class="concurrency:k_means" compatibility="9.0.001" expanded="true" height="82" name="Clustering" origin="GENERATED_TUTORIAL" 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="2"/>
        <parameter key="max_runs" value="10"/>
        <parameter key="determine_good_start_values" value="false"/>
        <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="operator_toolbox:extract_statistics" compatibility="1.7.000" expanded="true" height="82" name="Extract Statistics" width="90" x="447" y="34">
        <parameter key="attribute_filter_type" value="single"/>
        <parameter key="attribute" value="cluster"/>
        <parameter key="attributes" value=""/>
        <parameter key="use_except_expression" value="false"/>
        <parameter key="value_type" value="attribute_value"/>
        <parameter key="use_value_type_exception" value="false"/>
        <parameter key="except_value_type" value="time"/>
        <parameter key="block_type" value="attribute_block"/>
        <parameter key="use_block_type_exception" value="false"/>
        <parameter key="except_block_type" value="value_matrix_row_start"/>
        <parameter key="invert_selection" value="false"/>
        <parameter key="include_special_attributes" value="true"/>
      </operator>
      <operator activated="true" class="aggregate" compatibility="9.2.000" expanded="true" height="82" name="Aggregate" width="90" x="581" y="34">
        <parameter key="use_default_aggregation" 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="attribute_value"/>
        <parameter key="use_value_type_exception" value="false"/>
        <parameter key="except_value_type" value="time"/>
        <parameter key="block_type" value="attribute_block"/>
        <parameter key="use_block_type_exception" value="false"/>
        <parameter key="except_block_type" value="value_matrix_row_start"/>
        <parameter key="invert_selection" value="false"/>
        <parameter key="include_special_attributes" value="false"/>
        <parameter key="default_aggregation_function" value="average"/>
        <list key="aggregation_attributes">
          <parameter key="cluster" value="count"/>
        </list>
        <parameter key="group_by_attributes" value="cluster"/>
        <parameter key="count_all_combinations" value="false"/>
        <parameter key="only_distinct" value="false"/>
        <parameter key="ignore_missings" value="true"/>
      </operator>
      <operator activated="true" class="sort" compatibility="9.2.000" expanded="true" height="82" name="Sort" width="90" x="715" y="34">
        <parameter key="attribute_name" value="count(cluster)"/>
        <parameter key="sorting_direction" value="increasing"/>
      </operator>
      <connect from_op="Ripley-Set" from_port="output" to_op="Clustering" to_port="example set"/>
      <connect from_op="Clustering" from_port="clustered set" to_op="Extract Statistics" to_port="example set input"/>
      <connect from_op="Extract Statistics" from_port="original" to_op="Aggregate" to_port="example set input"/>
      <connect from_op="Aggregate" from_port="example set output" to_op="Sort" to_port="example set input"/>
      <connect from_op="Sort" 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>
    Hope this helps,

    Regards,

    Lionel

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