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User: Peter Jeszenszky

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Peter Jeszenszky

Choosing the best k value for the k-NN cla... (1)

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The process determines the best value for the parameter k for the k-NN classification of the Breast Cancer Wisconsin (Diagnostic) data set available in the UCI Machine Learning Repository. The optimal k is computed by using 10-fold cross-validation. (To get better results each cross-validation is repeated 10 times and the averages of the runs are considered.) Finally, a k-NN classifier is built and evaluated on the entire data set using the optimal k. During the process the resulting average ...

Created: 2012-09-28 | Last updated: 2012-09-28

RapidMiner

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Peter Jeszenszky

A simple process that demonstrates how to ... (1)

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This simple RapidMiner process demonstrates how to use the Open File operator introduced in RapidMiner 5.2. In this example we use the operator to consume a data feed from the web.

Created: 2012-09-27

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