Content from the RapidMiner Demo group

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Who Wants to be a Data Miner?

Created: 2011-11-02 17:54:07 | Last updated: 2013-09-09 16:22:11

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CamelCases (1)

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this process splits up camelcases

Created: 2010-06-02

Transaction Analysis Demo from RM 5 Intro Day (1)

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This is the demo process presented at the RapidMiner 5 Intro Day. It combines customer segmentation with direct mailing. It loads some transaction data, aggregates and pivotes the data so it can be used by a clustering to perform a customer segmentation. Then, additional data is joined with the clustered data. First, response/no-response data is joined, and them some additional information about the users is added. Finally, customers are classified into response/no-response classes. The dat...

Created: 2010-04-30 | Last updated: 2010-05-05

Stacking (1)

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RapidMiner supports Meta Learning by embedding one or several basic learners as children into a parent meta learning operator. Here, we use a three base learners inside the stacking operator: decision tree induction, linear regression, and a nearest neighbours classifier. Finally, a Naive Bayes learner is used as a stacking learner which uses the predictions of the preceeding three learners to make a combined prediction.

Created: 2010-04-29

Crossvalidation with SVM (1)

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Performs a crossvalidation on a given data set with nominal label, using a Support Vector Machine as a learning algorithm. Inside the cross validation, the first subprocess generates an SVM model, and the second subprocess evaluates it. applying it on a so-far unused subset of the data and counting the misclassifications.

Created: 2010-04-29