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Extract and save the items of each cluster in an Excel file

User: "ahootanha"
New Altair Community Member
Updated by Jocelyn

Hello
I kmeans clustered
I want to save the items of each cluster in an Excel file, but I do not know how to do it.
And
Is there a possibility of fuzzy clustering in the program?
Thanks

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    User: "lionelderkrikor"
    New Altair Community Member

    Hi @ahootanha,

     

    To answer to your first question, one method is to use the Filter Examples and Write Excel operators.

    Here an example of process with 3 clusters : 

    <?xml version="1.0" encoding="UTF-8"?><process version="8.1.000">
    <context>
    <input/>
    <output/>
    <macros/>
    </context>
    <operator activated="true" class="process" compatibility="8.1.000" expanded="true" name="Process">
    <process expanded="true">
    <operator activated="true" class="retrieve" compatibility="8.1.000" expanded="true" height="68" name="Retrieve Iris" width="90" x="112" y="34">
    <parameter key="repository_entry" value="//Samples/data/Iris"/>
    </operator>
    <operator activated="true" class="concurrency:k_means" compatibility="8.1.000" expanded="true" height="82" name="Clustering" width="90" x="313" y="34">
    <parameter key="k" value="3"/>
    </operator>
    <operator activated="true" class="filter_examples" compatibility="8.1.000" expanded="true" height="103" name="Filter Examples" width="90" x="514" y="34">
    <list key="filters_list">
    <parameter key="filters_entry_key" value="cluster.equals.cluster_0"/>
    </list>
    </operator>
    <operator activated="true" class="write_excel" compatibility="8.1.000" expanded="true" height="82" name="Write Excel" width="90" x="715" y="34">
    <parameter key="excel_file" value="C:\Users\Lionel\Documents\Formations_DataScience\Rapidminer\Tests_Rapidminer\Extract_cluster\cluster_0.xlsx"/>
    </operator>
    <operator activated="true" class="filter_examples" compatibility="8.1.000" expanded="true" height="103" name="Filter Examples (2)" width="90" x="514" y="187">
    <list key="filters_list">
    <parameter key="filters_entry_key" value="cluster.equals.cluster_1"/>
    </list>
    </operator>
    <operator activated="true" class="filter_examples" compatibility="8.1.000" expanded="true" height="103" name="Filter Examples (3)" width="90" x="514" y="340">
    <list key="filters_list">
    <parameter key="filters_entry_key" value="cluster.equals.cluster_2"/>
    </list>
    </operator>
    <operator activated="true" class="write_excel" compatibility="8.1.000" expanded="true" height="82" name="Write Excel (2)" width="90" x="715" y="187">
    <parameter key="excel_file" value="C:\Users\Lionel\Documents\Formations_DataScience\Rapidminer\Tests_Rapidminer\Extract_cluster\cluster_1.xlsx"/>
    </operator>
    <operator activated="true" class="write_excel" compatibility="8.1.000" expanded="true" height="82" name="Write Excel (3)" width="90" x="715" y="340">
    <parameter key="excel_file" value="C:\Users\Lionel\Documents\Formations_DataScience\Rapidminer\Tests_Rapidminer\Extract_cluster\cluster_2.xlsx"/>
    </operator>
    <connect from_op="Retrieve Iris" from_port="output" to_op="Clustering" to_port="example set"/>
    <connect from_op="Clustering" from_port="clustered set" to_op="Filter Examples" to_port="example set input"/>
    <connect from_op="Filter Examples" from_port="example set output" to_op="Write Excel" to_port="input"/>
    <connect from_op="Filter Examples" from_port="original" to_op="Filter Examples (2)" to_port="example set input"/>
    <connect from_op="Write Excel" from_port="through" to_port="result 1"/>
    <connect from_op="Filter Examples (2)" from_port="example set output" to_op="Write Excel (2)" to_port="input"/>
    <connect from_op="Filter Examples (2)" from_port="original" to_op="Filter Examples (3)" to_port="example set input"/>
    <connect from_op="Filter Examples (3)" from_port="example set output" to_op="Write Excel (3)" to_port="input"/>
    <connect from_op="Write Excel (2)" from_port="through" to_port="result 2"/>
    <connect from_op="Write Excel (3)" from_port="through" to_port="result 3"/>
    <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>

    To answer to your second question, I don't know what is "fuzzy clustering", but

    if you don't know, a priori, the number of cluster(s), you can use the X-Means operator : This model determine

    the correct number of cluster(s) based on the Bayesian Information Criteria (BIC).

     

    I hope it helps,

     

    Regards,

     

    Lionel

     

    User: "lionelderkrikor"
    New Altair Community Member

    Hi again @ahootanha,

     

    To better answer to your first question, you can find here a more flexible process

    using the Loop Values operator : it is independant of the number of cluster(s).

    <?xml version="1.0" encoding="UTF-8"?><process version="8.1.000">
    <context>
    <input/>
    <output/>
    <macros/>
    </context>
    <operator activated="true" class="process" compatibility="8.1.000" expanded="true" name="Process">
    <process expanded="true">
    <operator activated="true" class="retrieve" compatibility="8.1.000" expanded="true" height="68" name="Retrieve Iris" width="90" x="112" y="34">
    <parameter key="repository_entry" value="//Samples/data/Iris"/>
    </operator>
    <operator activated="true" class="concurrency:k_means" compatibility="8.1.000" expanded="true" height="82" name="Clustering" width="90" x="246" y="34">
    <parameter key="k" value="3"/>
    </operator>
    <operator activated="true" class="concurrency:loop_values" compatibility="8.1.000" expanded="true" height="82" name="Loop Values" width="90" x="447" y="34">
    <parameter key="attribute" value="cluster"/>
    <process expanded="true">
    <operator activated="true" class="filter_examples" compatibility="8.1.000" expanded="true" height="103" name="Filter Examples" width="90" x="246" y="34">
    <list key="filters_list">
    <parameter key="filters_entry_key" value="cluster.equals.%{loop_value}"/>
    </list>
    </operator>
    <operator activated="true" class="write_excel" compatibility="8.1.000" expanded="true" height="82" name="Write Excel" width="90" x="514" y="34">
    <parameter key="excel_file" value="C:\Users\Lionel\Documents\Formations_DataScience\Rapidminer\Tests_Rapidminer\Extract_cluster\%{loop_value}.xlsx"/>
    </operator>
    <connect from_port="input 1" to_op="Filter Examples" to_port="example set input"/>
    <connect from_op="Filter Examples" from_port="example set output" to_op="Write Excel" to_port="input"/>
    <connect from_op="Write Excel" from_port="through" to_port="output 1"/>
    <portSpacing port="source_input 1" spacing="0"/>
    <portSpacing port="source_input 2" spacing="0"/>
    <portSpacing port="sink_output 1" spacing="0"/>
    <portSpacing port="sink_output 2" spacing="0"/>
    </process>
    </operator>
    <connect from_op="Retrieve Iris" from_port="output" to_op="Clustering" to_port="example set"/>
    <connect from_op="Clustering" from_port="clustered set" to_op="Loop Values" to_port="input 1"/>
    <connect from_op="Loop Values" from_port="output 1" 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>

    Regards,

     

     

    Lionel

     

    User: "ahootanha"
    New Altair Community Member
    OP

    Hello
    thank you very much
    But
    I do not know where to use these code in my  rapidminer program?
    Please guide
    Send me a screenshot of the implementation of operators
    Thanks

    User: "ahootanha"
    New Altair Community Member
    OP

    look
    The field to choose the name of the clusters is empty
    Help me please

    12.jpg

    User: "Thomas_Ott"
    New Altair Community Member

    @ahootanha did you search for this problem on the threads? It's probably due to the meta-data not propograting correctly. You can type in the attribute name (case sensitive) and it will work.