Compute Mean Value of Each Cluster for an Ignored Attribute

goh_han_pingoh_han_pin Member Posts: 1 Contributor I
edited November 2018 in Help

During clustering,

how do I ignore an attribute

then later display the average value of that ignored attitude for each cluster?

                 

My scenario as follows:

I have a dataset.

Each example is a student, with a set of attributes.

The attributes are the student’s ‘input’ characteristics, and one attribute being the student’s achievement test scores.

 

How do I ignore the student’s test scores during clustering, so that cluster is merely done based on student’s input characteristics?

But, at the end of the clustering process, link the students in each cluster to their achievement test scores, and compute the mean (average) test scores for the students from each cluster?

 

H P

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Answers

  • lionelderkrikorlionelderkrikor Moderator, RapidMiner Certified Analyst, Member Posts: 716   Unicorn

    Hi @goh_han_pin,

     

    Can you share your dataset, please, in order to test a possible process which answer to your project ?

     

    Regards,

     

    Lionel

  • mschmitzmschmitz Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, University Professor Posts: 2,030  RM Data Scientist

    Hi,

     

    The attached process should do it

     

    Best,

    MArtin

     

    <?xml version="1.0" encoding="UTF-8"?><process version="8.0.001">
    <context>
    <input/>
    <output/>
    <macros/>
    </context>
    <operator activated="true" class="process" compatibility="8.0.001" expanded="true" name="Process">
    <process expanded="true">
    <operator activated="true" class="retrieve" compatibility="8.0.001" expanded="true" height="68" name="Retrieve Sonar" width="90" x="112" y="34">
    <parameter key="repository_entry" value="//Samples/data/Sonar"/>
    </operator>
    <operator activated="true" class="set_role" compatibility="8.0.001" expanded="true" height="82" name="Set Role" width="90" x="246" y="34">
    <parameter key="attribute_name" value="attribute_1"/>
    <parameter key="target_role" value="xx"/>
    <list key="set_additional_roles"/>
    <description align="center" color="transparent" colored="false" width="126">Exclude attribute_1 for clustering</description>
    </operator>
    <operator activated="true" class="x_means" compatibility="8.0.001" expanded="true" height="82" name="X-Means" width="90" x="447" y="34"/>
    <operator activated="true" class="aggregate" compatibility="8.0.001" expanded="true" height="82" name="Aggregate" width="90" x="581" y="34">
    <list key="aggregation_attributes">
    <parameter key="attribute_1" value="average"/>
    </list>
    <parameter key="group_by_attributes" value="cluster"/>
    </operator>
    <connect from_op="Retrieve Sonar" from_port="output" to_op="Set Role" to_port="example set input"/>
    <connect from_op="Set Role" from_port="example set output" to_op="X-Means" to_port="example set"/>
    <connect from_op="X-Means" from_port="clustered set" to_op="Aggregate" to_port="example set input"/>
    <connect from_op="Aggregate" 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>
    - Head of Data Science Services at RapidMiner -
    Dortmund, Germany
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