R: precrec: A package for computing accurate ROC and...

precrec {precrec} | R Documentation

## precrec: A package for computing accurate ROC and Precision-Recall curves

### Description

The precrec package contains several functions and `S3` generics to provide a robust platform for performance evaluation of binary classifiers.

### Functions

The precrec package provides the following six functions.

Function | Description
`evalmod` | Main function to calculate evaluation measures
`mmdata` | Reformat input data for performance evaluation calculation
`join_scores` | Join scores of multiple models into a list
`join_labels` | Join observed labels of multiple test datasets into a list
`create_sim_samples` | Create random samples for simulations
`format_nfold` | Create n-fold cross validation dataset from data frame

### S3 generics

The precrec package provides eight different `S3` generics for the `S3` objects generated by the `evalmod` function.

S3 generic | Library | Description
`print` | base | Print the calculation results and the summary of the test data
`as.data.frame` | base | Convert a precrec object to a data frame
`plot` | graphics | Plot performance evaluation measures
`autoplot` | ggplot2 | Plot performance evaluation measures with ggplot2
`fortify` | ggplot2 | Prepare a data frame for ggplot2
`auc` | precrec | Make a data frame with AUC scores
`part` | precrec | Calculate partial curves and partial AUC scores
`pauc` | precrec | Make a data frame with pAUC scores

### Performance measure calculations

The `evalmod` function calculates ROC and Precision-Recall curves and returns an `S3` object. The generated `S3` object can be used with several different `S3` generics, such as `print` and `plot`. The `evalmod` function can also calculate basic evaluation measures - error rate, accuracy, specificity, sensitivity, precision, Matthews correlation coefficient, and F-Score.

### Data preparation

The `mmdata` function creates an input dataset for the `evalmod` function. The generated dataset contains formatted scores and labels.

`join_scores` and `join_labels` are helper functions to combine multiple scores and labels.

The `create_sim_samples` function creates test datasets with five different performance levels.

### Data visualization

`plot` takes an `S3` object generated by `evalmod` as input and plot corresponding curves.

`autoplot` uses `ggplot` to plot curves.

### Result retrieval

`as.data.frame` takes an `S3` object generated by `evalmod` as input and and returns a data frame with calculated curve points.

`auc` and `pauc` returns a data frame with AUC scores and partial AUC scores, respectively.

[Package precrec version 0.9.1 Index]