scorer: Computes various predictive performance scores between two...

In genpack/maler: A package for building pipelines of Machine Learning models.

Computes various predictive performance scores between two binary columns of a table

Description

Computes various predictive performance scores between two binary columns of a table

Usage

scorer(df, prediction_col, actual_col)

Value

list containing various scores. Returned scores are: tp (True Positive), tn (True Negative), fp (False Positive), fn (False Negative), tpr (True Positive Rate) or recall ro sensitivity or hit_rate, fnr (False Negative Rate) or miss_rate, tnr (True Negative Rate) or specificity or selectivity fpr (False Positive Rate) or fall_out, ppv (Positive Predictive Value) or precision fdr (False Discovery Rate), for (False Omission Rate), pt (Prevalence Threshold), ts (Threat Score) or csi (Critical Success Index) accuracy, ba (Balanced Accuracy) f1 (F1 Score), fmi (Fowlkes–Mallows Index), informedness, markedness mcc (Matthews Correlation Coefficient) lift

Fields

df

data.frame, tibble, data.table or matrix: Input table containing at least two columns with binary data

prediction_col

character header of the column containing predicted binary classes

actual_col

character header of the column containing actual binary classes

genpack/maler documentation built on Jan. 27, 2025, 1:23 p.m.