This category contains 5635 nodes.
Class for constructing a random forest.
A tree that considers K randomly chosen attributes at each node.
Class that implements a radial basis function network.
Checks structures and tries to normalize them, if necessary.
Read PNG images from a list of URLs and append them as a new column.
Predicts the response using a regression model.
Fast decision tree learner.
The implementation of a RIpple-DOwn rule learner.
Node to replace the RowID and/or to create a column with the values of the current RowID.
Applies user-defined business rules to the input table
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