metric_PrecisionRecall: metric_PrecisionRecall

In gloverd2/admr: Contains standard functions for Admiral Advance Analytics

Description

Return Weighted mean of precisions achieved at each threshold

Usage

metric_PrecisionRecall(actual, predicted, weight = NULL, na.rm = FALSE)

Arguments

actual	Array[Numeric] - 0 or 1 - Values we are aiming to predict.
predicted	Array[Numeric] / DataFrame[Numeric] - Between 0 and 1 - Values that we have predicted.
weight	Optional: Array[Numeric] - Weighting of predictions. If NULL even weighting is used.
na.rm	logical. Should missing values be removed?

Value

Weighted mean of precisions achieved at each threshold, with the increase in recall from the previous threshold used as the weight. Single value if predicted is vector. Named list if predicted is dataframe.

See Also

plot_PrecisionRecall

Examples

data <- data.frame(x1=runif(100), x2=runif(100), noise=rnorm(100, sd=0.2)) %>%
  mutate(target=ifelse(x1 + noise>0.5, 1, 0))

metric_PrecisionRecall(actual=data$target, predicted=data$x1)
metric_PrecisionRecall(actual=data$target, predicted=data[c("x1","x2")])

gloverd2/admr documentation built on Dec. 2, 2020, 11:16 p.m.