"[solved]K means clustering for text data to cluster similar data"

nachiketnachiket Member Posts: 6 Contributor II
edited June 2019 in Help
Hello I am new rapidminer

I have taken sample data as (for general study purpose)

Task
a
a
a
a
f
f
f
f
f
d
d
d
r
r
d
.
.
.
(repeating these characters i.e. "a", "r"," d"," f")


in excel file

and now I am applying kmeans clustering with 4 cluster (as I used 4 characters)

for smaller number of occurrences of "a" "r" "d" "f" when almost evenly distributed it works fine

but when a particular character dominates one cluster becomes empty and others are filled

what should be used in-order to avoid this situation ?  






this is what I tried






<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<process version="5.1.011">
 <context>
   <input/>
   <output/>
   <macros/>
 </context>
 <operator activated="true" class="process" compatibility="5.1.011" expanded="true" name="Process">
   <process expanded="true" height="396" width="751">
     <operator activated="true" class="read_excel" compatibility="5.1.011" expanded="true" height="60" name="Read Excel" width="90" x="45" y="75">
       <parameter key="excel_file" value="C:\Users\hp\Desktop\tempclusterdel.xls"/>
       <parameter key="imported_cell_range" value="A1:A54"/>
       <parameter key="first_row_as_names" value="false"/>
       <list key="annotations">
         <parameter key="0" value="Name"/>
       </list>
       <list key="data_set_meta_data_information">
         <parameter key="0" value="Task.true.text.attribute"/>
       </list>
     </operator>
     <operator activated="true" class="generate_id" compatibility="5.1.011" expanded="true" height="76" name="Generate ID" width="90" x="71" y="142"/>
     <operator activated="true" class="multiply" compatibility="5.1.011" expanded="true" height="94" name="Multiply" width="90" x="112" y="210"/>
     <operator activated="true" class="nominal_to_numerical" compatibility="5.1.011" expanded="true" height="94" name="Nominal to Numerical" width="90" x="179" y="30">
       <list key="comparison_groups"/>
     </operator>
     <operator activated="true" class="multiply" compatibility="5.1.011" expanded="true" height="94" name="Multiply (2)" width="90" x="312" y="94"/>
     <operator activated="true" class="k_means" compatibility="5.1.011" expanded="true" height="76" name="Clustering" width="90" x="447" y="75">
       <parameter key="k" value="4"/>
     </operator>
     <operator activated="true" class="join" compatibility="5.1.011" expanded="true" height="76" name="Join" width="90" x="514" y="210">
       <list key="key_attributes"/>
     </operator>
     <connect from_op="Read Excel" from_port="output" to_op="Generate ID" to_port="example set input"/>
     <connect from_op="Generate ID" from_port="example set output" to_op="Multiply" to_port="input"/>
     <connect from_op="Multiply" from_port="output 1" to_op="Nominal to Numerical" to_port="example set input"/>
     <connect from_op="Multiply" from_port="output 2" to_op="Join" to_port="left"/>
     <connect from_op="Nominal to Numerical" from_port="example set output" to_op="Multiply (2)" to_port="input"/>
     <connect from_op="Multiply (2)" from_port="output 1" to_op="Clustering" to_port="example set"/>
     <connect from_op="Multiply (2)" from_port="output 2" to_port="result 3"/>
     <connect from_op="Clustering" from_port="cluster model" to_port="result 2"/>
     <connect from_op="Clustering" from_port="clustered set" to_op="Join" to_port="right"/>
     <connect from_op="Join" from_port="join" 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"/>
     <portSpacing port="sink_result 3" spacing="0"/>
     <portSpacing port="sink_result 4" spacing="0"/>
   </process>
 </operator>
</process>

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