softening.by.esd {SplitSoftening}

Soften splits separately using error standard deviation.

Description

Set boundaries determined by given data to the splits in the tree, such that in any inner node if its splitting value would be moved there, then the number of misclassified cases in this node would be one standard deviation over the actual misclassification.

Usage

softening.by.esd(fit, d)

Arguments

fit

The soft tree

d

The data set

Details

This is the same approach as C4.5 uses for "probabilistic splits"

References

Quinlan, J. Ross (1993), C4.5: programs for machine learning, San Francisco, CA, USA: Morgan Kaufmann Publishers Inc.