Learn R Programming

MLeval (version 0.3)

Machine Learning Model Evaluation

Description

Straightforward and detailed evaluation of machine learning models. 'MLeval' can produce receiver operating characteristic (ROC) curves, precision-recall (PR) curves, calibration curves, and PR gain curves. 'MLeval' accepts a data frame of class probabilities and ground truth labels, or, it can automatically interpret the Caret train function results from repeated cross validation, then select the best model and analyse the results. 'MLeval' produces a range of evaluation metrics with confidence intervals.

Copy Link

Version

Install

install.packages('MLeval')

Monthly Downloads

576

Version

0.3

License

AGPL-3

Maintainer

Christopher John

Last Published

February 12th, 2020

Functions in MLeval (0.3)

preds

Predictions from gbm on the Sonar test data
predsc

Predictions from gbm and random forest on the Sonar test data
brier_score

brier_score: A Brier score function
fit2

Gradient boosted machines fitted object from Caret on Sonar data
LL

LL: Log-likelihood function
im_fit

Random forest fitted object from Caret on simulated imbalanced data
fit

Random forest fitted object from Caret on Sonar data
evalm

evalm: Evaluate Machine Learning Models in R
fit3

Random forest fitted object from Caret on Sonar data with log-likelihood objective function
fit1

Random forest fitted object from Caret on Sonar data
Sonar

Sonar data