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DBSCAN results

TheBearTheBear Member Posts: 18 Maven
edited November 2018 in Help
as far as I understood DBSCAN, there should be core points, border points and noise.
I wonder how to identify the borderpoints in the results tab.? I refer to the explanation found here:
Any help on that?

Maybe I am wrong but it seems to me that not in all cases the Cluster_0 is filled with noise.
I just quick checked with R [fpc package] an easy example where NO noise should occur.
However the cluster_0 is existent in rapidminer. I guess its a valid cluster result rather than noise.

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82 440 110
75 380 20
72 390 25
76 375 85
72 395 30
93 435 80
78 438 160
<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<process version="5.2.002">
  <operator activated="true" class="process" compatibility="5.2.002" expanded="true" name="Process">
    <process expanded="true" height="622" width="955">
      <operator activated="true" class="read_csv" compatibility="5.2.002" expanded="true" height="60" name="Read CSV" width="90" x="45" y="120">
        <parameter key="csv_file" value="3d_data_SOM.csv"/>
        <parameter key="column_separators" value=","/>
        <parameter key="first_row_as_names" value="false"/>
        <list key="annotations">
          <parameter key="0" value="Name"/>
        <parameter key="encoding" value="windows-1252"/>
        <list key="data_set_meta_data_information">
          <parameter key="0" value="Lotpastenvolumen.true.integer.attribute"/>
          <parameter key="1" value="Standoff.true.integer.attribute"/>
          <parameter key="2" value="Voids.true.integer.attribute"/>
          <parameter key="3" value="Klasse.true.polynominal.attribute"/>
          <parameter key="4" value="Training-Test.true.binominal.attribute"/>
          <parameter key="5" value="KNN-Vorhersage.true.polynominal.attribute"/>
      <operator activated="true" class="generate_id" compatibility="5.2.002" expanded="true" height="76" name="Generate ID" width="90" x="179" y="300"/>
      <operator activated="true" class="normalize" compatibility="5.2.002" expanded="true" height="94" name="Normalize (2)" width="90" x="313" y="255">
        <parameter key="attribute_filter_type" value="subset"/>
        <parameter key="attributes" value="Lotpastenvolumen|Standoff|Voids"/>
        <parameter key="method" value="range transformation"/>
      <operator activated="true" class="select_attributes" compatibility="5.2.002" expanded="true" height="76" name="Select Attributes" width="90" x="447" y="210">
        <parameter key="attribute_filter_type" value="subset"/>
        <parameter key="attributes" value="|Lotpastenvolumen|Standoff|Voids"/>
      <operator activated="true" class="dbscan" compatibility="5.2.002" expanded="true" height="76" name="Clustering" width="90" x="648" y="210">
        <parameter key="epsilon" value="0.43"/>
        <parameter key="min_points" value="3"/>
        <parameter key="measure_types" value="NumericalMeasures"/>
      <operator activated="true" class="join" compatibility="5.2.002" expanded="true" height="76" name="Join" width="90" x="715" y="390">
        <list key="key_attributes"/>
      <operator activated="true" class="select_attributes" compatibility="5.2.002" expanded="true" height="76" name="Select Attributes (2)" width="90" x="849" y="300">
        <parameter key="attribute_filter_type" value="subset"/>
        <parameter key="attributes" value="Lotpastenvolumen|Standoff|Voids||cluster|Klasse"/>
      <connect from_op="Read CSV" from_port="output" to_op="Generate ID" to_port="example set input"/>
      <connect from_op="Generate ID" from_port="example set output" to_op="Normalize (2)" to_port="example set input"/>
      <connect from_op="Normalize (2)" from_port="example set output" to_op="Select Attributes" to_port="example set input"/>
      <connect from_op="Normalize (2)" from_port="original" to_op="Join" to_port="left"/>
      <connect from_op="Select Attributes" from_port="example set output" to_op="Clustering" to_port="example set"/>
      <connect from_op="Clustering" from_port="cluster model" to_port="result 1"/>
      <connect from_op="Clustering" from_port="clustered set" to_op="Join" to_port="right"/>
      <connect from_op="Join" from_port="join" to_op="Select Attributes (2)" to_port="example set input"/>
      <connect from_op="Select Attributes (2)" from_port="example set output" to_port="result 2"/>
      <portSpacing port="source_input 1" spacing="0"/>
      <portSpacing port="sink_result 1" spacing="0"/>
      <portSpacing port="sink_result 2" spacing="0"/>
      <portSpacing port="sink_result 3" spacing="0"/>
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