calc_performance_metrics: Compute performance metrics

In pridiltal/oddwater: Outlier Detection in Data from Water-Quality Sensors

Description

Computes various measure to evaluate the performance of an algorithm

Usage

calc_performance_metrics(y_truth, y_output, pos_label, neg_label,
  print_out = TRUE)

Arguments

y_truth	A character vector containing the gorund truth
y_output	a character vector containing the predicted labels from the algorithm
pos_label	A character string. Label used to indicate the outliers in the original dataframe.
neg_label	A character string. Label used to indicate the typical values in the original dataframe.
print_out	If TRUE, output will be printed to console.

Value

A list with the following elements:

TN	True negatives
FN	False negatives
FP	False positives
TP	True positives
Accuracy	Accuracy
Error_Rate	Error Rate
Sensitivity	Sensitivity
Specificity	Specificity
Precision	Precision
Recall	Recall
F_Measure	F Measure
Optimised_Precision	Optimised Precision
PPV	Positive Predictive Value
NPV	Negative Predictive Value

Author(s)

Priyanga Dilini Talagala

Examples

true_labels <- c("out", "out", "normal", "out", "normal", "normal",
                 "normal", "normal", "normal", "normal")
output <- c("out", "normal", "normal", "normal", "out", "out",
            "normal", "normal", "normal", "normal")
out<- calc_performance_metrics(y_truth = true_labels, y_output = output,
                              pos_label = "out", neg_label = "normal")

pridiltal/oddwater documentation built on Dec. 18, 2019, 8:18 p.m.