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MLeval (version 0.1)

Machine Learning Model Evaluation

Description

Straightforward and detailed evaluation of machine learning models. 'MLeval' can produce receiver operating characteristic curves (ROCs), precision-recall (PR) curves, and PR gain curves. 'MLeval' can automatically interpret the Caret train function results from repeated cross validation, select the best model, and produces a number of evaluation metrics with confidence intervals.

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Version

Install

install.packages('MLeval')

Monthly Downloads

712

Version

0.1

License

AGPL-3

Maintainer

Christopher John

Last Published

November 25th, 2019

Functions in MLeval (0.1)

predsc

Predictions from gbm and random forest on the Sonar test data
fit3

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

LL: Log-likelihood function
preds

Predictions from gbm on the Sonar test data
Sonar

Sonar data
im_fit

Random forest fitted object from Caret on simulated imbalanced data
fit2

Gradient boosted machines fitted object from Caret on Sonar data
fit1

Random forest fitted object from Caret on Sonar data
brier_score

brier_score: A Brier score function
fit

Random forest fitted object from Caret on Sonar data
evalm

evalm: Evaluate Machine Learning Models in R