BinarybalancedCut: Threshold Cut Point of Probability for a Binary Classifier Model

Allows to view the optimal probability cut-off point at which the Sensitivity and Specificity meets and its a best way to minimize both Type-1 and Type-2 error for a binary Classifier in determining the Probability threshold.

Version:	0.2
Imports:	ggplot2, reshape2
Suggests:	knitr
Published:	2017-09-02
Author:	Navinkumar Nedunchezhian
Maintainer:	Navinkumar Nedunchezhian <navinkumar.nedunchezhian at gmail.com>
License:	GPL-2
NeedsCompilation:	no
CRAN checks:	BinarybalancedCut results

Documentation:

Reference manual:

BinarybalancedCut.pdf

Downloads:

Package source:	BinarybalancedCut_0.2.tar.gz
Windows binaries:	r-devel: BinarybalancedCut_0.2.zip, r-release: BinarybalancedCut_0.2.zip, r-oldrel: BinarybalancedCut_0.2.zip
macOS binaries:	r-release (arm64): BinarybalancedCut_0.2.tgz, r-oldrel (arm64): BinarybalancedCut_0.2.tgz, r-release (x86_64): BinarybalancedCut_0.2.tgz, r-oldrel (x86_64): BinarybalancedCut_0.2.tgz

Linking:

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