"Export (FP growth) frequentitemsets output into a CSV table"
sebastian_gonza
RapidMiner Certified Analyst, MemberPosts:52Guru
Best Answers
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JEdward RapidMiner Certified Analyst, RapidMiner Certified Expert, MemberPosts:578Unicorn
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 & 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 "product purchased yes/no " 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> 0 -
MartinLiebig Administrator, Moderator, Employee, RapidMiner Certified Analyst, RapidMiner Certified Expert, University ProfessorPosts:3,362RM Data Scientist
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, Germany0
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Dortmund, Germany