How to create ClusterModel from ExampleSet

PiccoloPaolo · July 2019

Hello everybody,

I have the following problem. I am trying to apply an iterative clustering in a naive approach. I cluster once using 2-means and then I apply 2-means to every generated cluster. I am wondering:

1) is there a more efficient way to do this? I tried the loop cluster operator but I failed.

2) is it possible to generate a ClusterModel from the ExampleSet returned by Append? This would be useful to launch a ClusterModelVisualizer and some scripts that need both ClusterModel and ExampleSet.

Thanks to everyone who will help me.

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y="85"><br>        <parameter key="add_cluster_attribute" value="true"/><br>        <parameter key="add_as_label" value="false"/><br>        <parameter key="remove_unlabeled" value="false"/><br>        <parameter key="k" value="2"/><br>        <parameter key="max_runs" value="10"/><br>        <parameter key="determine_good_start_values" value="true"/><br>        <parameter key="measure_types" value="BregmanDivergences"/><br>        <parameter key="mixed_measure" value="MixedEuclideanDistance"/><br>        <parameter key="nominal_measure" value="NominalDistance"/><br>        <parameter key="numerical_measure" value="EuclideanDistance"/><br>        <parameter key="divergence" value="SquaredEuclideanDistance"/><br>        <parameter key="kernel_type" value="radial"/><br>        <parameter key="kernel_gamma" value="1.0"/><br>        <parameter key="kernel_sigma1" value="1.0"/><br>        <parameter key="kernel_sigma2" value="0.0"/><br>        <parameter key="kernel_sigma3" value="2.0"/><br>        <parameter key="kernel_degree" value="3.0"/><br>        <parameter key="kernel_shift" value="1.0"/><br>        <parameter key="kernel_a" value="1.0"/><br>        <parameter key="kernel_b" value="0.0"/><br>        <parameter key="max_optimization_steps" value="100"/><br>        <parameter key="use_local_random_seed" value="false"/><br>        <parameter key="local_random_seed" value="1992"/><br>      </operator><br>      <operator activated="true" class="multiply" compatibility="9.3.001" expanded="true" height="103" name="Multiply" width="90" x="313" y="85"/><br>      <operator activated="true" class="filter_examples" compatibility="9.3.001" expanded="true" height="103" name="Filter Examples" width="90" x="447" y="85"><br>        <parameter key="parameter_expression" value=""/><br>        <parameter key="condition_class" value="custom_filters"/><br>        <parameter key="invert_filter" value="false"/><br>        <list key="filters_list"><br>          <parameter key="filters_entry_key" value="cluster.equals.cluster_0"/><br>        </list><br>        <parameter key="filters_logic_and" value="true"/><br>        <parameter key="filters_check_metadata" value="true"/><br>      </operator><br>      <operator activated="true" class="concurrency:k_means" compatibility="9.3.001" expanded="true" height="82" name="Clustering (2)" width="90" x="581" y="85"><br>        <parameter key="add_cluster_attribute" value="true"/><br>        <parameter key="add_as_label" value="false"/><br>        <parameter key="remove_unlabeled" value="false"/><br>        <parameter key="k" value="2"/><br>        <parameter key="max_runs" value="10"/><br>        <parameter key="determine_good_start_values" value="true"/><br>        <parameter key="measure_types" value="BregmanDivergences"/><br>        <parameter key="mixed_measure" value="MixedEuclideanDistance"/><br>        <parameter key="nominal_measure" value="NominalDistance"/><br>        <parameter key="numerical_measure" value="EuclideanDistance"/><br>        <parameter key="divergence" value="SquaredEuclideanDistance"/><br>        <parameter key="kernel_type" value="radial"/><br>        <parameter key="kernel_gamma" value="1.0"/><br>        <parameter key="kernel_sigma1" value="1.0"/><br>        <parameter key="kernel_sigma2" value="0.0"/><br>        <parameter key="kernel_sigma3" value="2.0"/><br>        <parameter key="kernel_degree" value="3.0"/><br>        <parameter key="kernel_shift" value="1.0"/><br>        <parameter key="kernel_a" value="1.0"/><br>        <parameter key="kernel_b" value="0.0"/><br>        <parameter key="max_optimization_steps" value="100"/><br>        <parameter key="use_local_random_seed" value="false"/><br>        <parameter key="local_random_seed" value="1992"/><br>      </operator><br>      <operator activated="true" class="filter_examples" compatibility="9.3.001" expanded="true" height="103" name="Filter Examples (2)" width="90" x="447" y="187"><br>        <parameter 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 <connect from_op="Clustering (3)" from_port="clustered set" to_op="Set Role" to_port="example set input"/><br>      <connect from_op="Set Role" from_port="example set output" to_op="Replace" to_port="example set input"/><br>      <connect from_op="Replace" from_port="example set output" to_op="Replace (2)" to_port="example set input"/><br>      <connect from_op="Replace (2)" from_port="example set output" to_op="Set Role (2)" to_port="example set input"/><br>      <connect from_op="Set Role (2)" from_port="example set output" to_op="Append" to_port="example set 2"/><br>      <connect from_op="Append" from_port="merged set" to_port="result 1"/><br>      <portSpacing port="source_input 1" spacing="0"/><br>      <portSpacing port="sink_result 1" spacing="0"/><br>      <portSpacing port="sink_result 2" spacing="0"/><br>    </process><br>  </operator><br></process><br><br>