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modeval (version 0.1.3)

Evaluation of Classification Model Options

Description

Designed to assist novice to intermediate analysts in choosing an optimal classification model, particularly for working with relatively small data sets. It provides cross-validated results comparing several different models at once using a consistent set of performance metrics, so users can hone in on the most promising approach rather than attempting single model fittings at a time. The package predefined 12 most common classification models, although users are free to select from the 200+ other options available in caret package.

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Install

install.packages('modeval')

Monthly Downloads

8

Version

0.1.3

License

CC0

Maintainer

Younggun You

Last Published

April 11th, 2017

Functions in modeval (0.1.3)

suggest_probCut

Compare Class Probability Distribution based on Probability Cut-off
suggest_probPop

Compare class probability distributions based on the population.
add_model

Add predictive models to Summary list.
add_prob

Add Class Probability
suggest_accuracy

Compare performance based on accuracy metrics.
suggest_auc

Compare performance based on Area Under the Curve, Sensitivity, and
suggest_category

Compare model performance by model category from
suggest_gain

Plot Gain Chart and Lift Chart
suggest_transformation

Plot Skewness and Kurtosis and suggest transformations
suggest_variable

Compare variables by importance.