Peter Jeszenszky's Workflows

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 ...

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.