plot_PrecisionRecall: plot_PrecisionRecall

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

Description

Returns a plot showing the Precision-Recall curve of one or more models compared to the Null model

#' Note: Predictions should be annualised (independent of exposure)

Usage

plot_PrecisionRecall(
  actual,
  predicted,
  weight = NULL,
  na.rm = FALSE,
  use_plotly = TRUE
)

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?
use_plotly	Optional: boolean - If TRUE plotly object is returned else ggplot2 object

Value

plotly object of showing Precision-Recall curve for all predictions given

See Also

metric_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))

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

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