DBSCAN results

TheBearTheBear Member Posts: 18  Maven
edited November 2018 in Help
Hi,
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: http://www-users.cs.umn.edu/~kumar/dmbook/ch8.pdf
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.

100 455 185
98 450 100
95 465 180
80 428 90
85 432 170
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">
  <context>
    <input/>
    <output/>
    <macros/>
  </context>
  <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"/>
        </list>
        <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"/>
        </list>
      </operator>
      <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>
      <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>
      <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>
      <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>
      <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"/>
      </operator>
      <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"/>
    </process>
  </operator>
</process>
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