statsFromConfusionMatrix: Accuracy, sensitivity, specificity, and precision of 2x2...

Description Usage Arguments Details Value

View source: R/performance.R

Description

In heuristica, "positive" means the row1 > row2. Other heuristica create confusion matrices with the expected layout, but below is documentation of that layout. A package like 'caret' offers a more general-purpose confusion matrix.

Usage

1
statsFromConfusionMatrix(confusion_matrix)

Arguments

confusion_matrix

A 2x2 confusion matrix.

Details

This assumes the input matrix is 2x2 and will STOP if not. It also assumes negatives are left and higher, and predictions are the rows, that is: true negative [-1,-1] false negative [-1,1] false negative [1, -1] true positive [1, 1]

The outputs are defined as: accuracy = (true positive + true negative) / all sensitivity = true positive rate = true positive / all positive (sensitivity is also called recall) specificity = true negative rate = true negative / all negative precision = positive predictive value = true positive

Value

A list with accuracy, sensitivity, specificity, and precision


heuristica documentation built on Sept. 8, 2021, 9:08 a.m.