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cutpointr (version 0.7.3)

Determine and Evaluate Optimal Cutpoints in Binary Classification Tasks

Description

Estimate cutpoints that optimize a specified metric in binary classification tasks and validate performance using bootstrapping. Some methods for more robust cutpoint estimation and various plotting functions are included.

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Version

Install

install.packages('cutpointr')

Monthly Downloads

1,889

Version

0.7.3

License

GPL-3

Maintainer

Christian Thiele

Last Published

April 13th, 2018

Functions in cutpointr (0.7.3)

Calculate Cohen's Kappa

print.cutpointr

Print cutpointr objects

multi_cutpointr

Calculate optimal cutpoints and further statistics for multiple predictors

Calculate the negative predictive value

Calculate number of knots to use in spline smoothing

false_omission_rate

Calculate the false omission and false discovery rate

maximize_spline_metric

Optimize a metric function in binary classification after spline smoothing

misclassification_cost

Calculate the misclassification cost

Plot the bootstrapped distribution of optimal cutpoints from a cutpointr object

Calculate the p-value of a chi-squared test

Determine and evaluate optimal cutpoints

maximize_loess_metric

Optimize a metric function in binary classification after LOESS smoothing

maximize_metric

Optimize a metric function in binary classification

print.multi_cutpointr

Print multi_cutpointr objects

Plot cutpointr objects

General purpose plotting function for cutpointr or roc_cutpointr objects

Plot a metric over all possible cutoffs from a cutpointr object

Calculate the positive or negative likelihood ratio

plot_metric_boot

Plot the bootstrapped metric distribution from a cutpointr object

plot_precision_recall

Precision recall plot from a cutpointr object

abs_d_sens_spec

Calculate the absolute difference of sensitivity and specificity

Calculate accuracy

Calculate precision

Plot ROC curve from a cutpointr object

Calculate the sum of sensitivity and specificity

Calculate the positive predictive value

Calculate the sum of positive and negative predictive value

Set a manual cutpoint for use with cutpointr

Calculate a ROC curve

Calculate specificity

Calculate true / false positive / negative rate

Suicide attempts and DSI sum scores of 532 subjects

Use the sample mean as cutpoint

predict.cutpointr

Predict using a cutpointr object

user_span_cutpointr

Calculate bandwidth for LOESS smoothing of metric functions by rule of thumb

Calculate the product of positive and negative predictive value

Use the sample median as cutpoint

Calculate sensitivity

Calculate the total utility

Calculate the product of sensitivity and specificity

oc_youden_kernel

Determine an optimal cutpoint maximizing the Youden-Index based on kernel smoothed densities

plot_sensitivity_specificity

Sensitivity and specificity plot from a cutpointr object

Plot the distribution of the independent variable per class from a cutpointr object

Extract number true / false positives / negatives

Calculate recall

Calculate the Youden-Index

Calculate the risk ratio (relative risk)

Extract the cutpoints from a ROC curve generated by cutpointr

maximize_boot_metric

Optimize a metric function in binary classification after bootstrapping

maximize_gam_metric

Optimize a metric function in binary classification after smoothing via generalized additive models

oc_youden_normal

Determine an optimal cutpoint for the Youden-Index assuming normal distributions

Calculate the F1-score

Calculate the odds ratio

Calculate the absolute difference of positive and negative predictive value

The standard evaluation version of cutpointr