"Export (FP growth) frequentitemsets output into a CSV table"

sebastian_gonzasebastian_gonza RapidMiner Certified Analyst, MemberPosts:52Guru
edited May 2019 inHelp

Hello

I tried exporting the result from (FP growth) frequentitemsets of the operator create association rules into a CSV file but I cant write it since it is not an object that can be converted to a table, how else can I do it if it is possible?

Thank you

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Best Answers

  • JEdwardJEdward RapidMiner Certified Analyst, RapidMiner Certified Expert, MemberPosts:578Unicorn
    索尔ution Accepted

    You can use the Reporting extension to extract it into an Excel document. Here's an example.




    < output/>


    < operator activated="true" class="process" compatibility="9.0.002" expanded="true" name="Process" origin="GENERATED_TEMPLATE">


    < operator activated="true" class="retrieve" compatibility="9.0.002" expanded="true" height="68" name="Load Transactions" origin="GENERATED_TEMPLATE" width="90" x="112" y="187">


    < operator activated="true" class="aggregate" compatibility="6.0.006" expanded="true" height="82" name="Aggregate" origin="GENERATED_TEMPLATE" width="90" x="112" y="336">





    < operator activated="true" class="pivot" compatibility="9.0.002" expanded="true" height="82" name="Pivot" origin="GENERATED_TEMPLATE" width="90" x="246" y="336">



    < operator activated="true" class="rename_by_replacing" compatibility="9.0.002" expanded="true" height="82" name="Rename by Replacing" origin="GENERATED_TEMPLATE" width="90" x="380" y="336">



    < operator activated="true" class="replace_missing_values" compatibility="9.0.002" expanded="true" height="103" name="Replace Missing Values" origin="GENERATED_TEMPLATE" width="90" x="112" y="442">



    < operator activated="true" class="numerical_to_binominal" compatibility="6.0.003" expanded="true" height="82" name="Numerical to Binominal" origin="GENERATED_TEMPLATE" width="90" x="246" y="442"/>
    < operator activated="true" class="set_role" compatibility="9.0.002" expanded="true" height="82" name="Set Role" origin="GENERATED_TEMPLATE" width="90" x="380" y="442">




    < operator activated="true" class="concurrency:fp_growth" compatibility="9.0.002" expanded="true" height="82" name="FP-Growth" origin="GENERATED_TEMPLATE" width="90" x="648" y="289">





    < operator activated="true" class="reporting:generate_report" compatibility="5.3.000" expanded="true" height="82" name="Generate Report" width="90" x="581" y="391">

    <参数键= "格式" value = "擅长" / >


    < operator activated="true" class="create_association_rules" compatibility="9.0.002" expanded="true" height="82" name="Create Association Rules" origin="GENERATED_TEMPLATE" width="90" x="715" y="493">


    < operator activated="true" class="reporting:report" compatibility="5.3.000" expanded="true" height="68" name="Report" width="90" x="782" y="391">



    <参数键= value =“reportable_type频繁的我tem Sets"/>










    < operator activated="true" class="reporting:report" compatibility="5.3.000" expanded="true" height="68" name="Report (2)" width="90" x="849" y="289">



    <参数键= value =“reportable_type频繁的我tem Sets"/>


















    MARKET BASKET ANALYSIS<br>Model associations between products by determining sets of items frequently purchased together and building association rules to derive recommendations.
    Step 1:<br/>Load transaction data containing a transaction id, a product id and a quantifier. The data denotes how many times a certain product has been purchased as part of a transactions.
    <br> <br> <br> <br> <br> <br> <br> <br> <br> <br> <br> <br> <br> Step 2:<br>Edit, transform &amp; load (ETL) - Aggregate transaction data to account for multiple occurrences of the same product in a transaction. Pivot the data so that each transaction is represented by a row. Transform purchase amounts to binary &quot;product purchased yes/no &quot; indicators.<br>
    Step 3:<br/>Using FP-Growth, determine frequent item sets. A frequent item sets denotes that the items (products) in the set have been purchased together frequently, i.e. in a certain ratio of transactions. This ratio is given by the support of the item set.
    <br> <br> <br> <br> <br> <br> Step 4:<br/>Create association rules which can be used for product recommendations depending on the confidences of the rules.<br>
    Outputs: association rules, frequent item set<br>



  • MartinLiebigMartinLiebig Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, University ProfessorPosts:3,362RM Data Scientist
    索尔ution Accepted

    Hi,

    converters extension got a converter for it to get it into an example set which can be written to anything.

    BR,

    martin

    - Head of Data Science Services at RapidMiner -
    Dortmund, Germany

Answers

  • kdafoekdafoe MemberPosts:18Maven
    Hi Martin.
    I know this is a little old, but could share what actual Converters Extension allows me to output the
    FP-Growth.frequent sets from the FP-Growth operator?I can use the one for association rules, but I can't find anything that works with frequency sets. Thanks, and I appreciate your knowledge share on the forum.

  • MartinLiebigMartinLiebig Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, University ProfessorPosts:3,362RM Data Scientist
    yes there is. The operator is called 'Item Sets to Data' and is part of the normal studio.

    Best,
    Martin

    - Head of Data Science Services at RapidMiner -
    Dortmund, Germany
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