threshOptim: threshOptim

In AdrianAntico/ModelingTools: AutoQuant

threshOptim

Description

threshOptim will return the utility maximizing threshold for future predictions along with the data generated to estimate the threshold

Usage

threshOptim(
  data,
  actTar = "target",
  predTar = "p1",
  tpProfit = 0,
  tnProfit = 0,
  fpProfit = -1,
  fnProfit = -2,
  MinThresh = 0.001,
  MaxThresh = 0.999,
  ThresholdPrecision = 0.001
)

Arguments

data	data is the data table you are building the modeling on
actTar	The column name where the actual target variable is located (in binary form)
predTar	The column name where the predicted values are located
tpProfit	This is the utility for generating a true positive prediction
tnProfit	This is the utility for generating a true negative prediction
fpProfit	This is the cost of generating a false positive prediction
fnProfit	This is the cost of generating a false negative prediction
MinThresh	Minimum value to consider for model threshold
MaxThresh	Maximum value to consider for model threshold
ThresholdPrecision	Incrementing value in search

Value

Optimal threshold and corresponding utilities for the range of thresholds tested

Author(s)

Adrian Antico

See Also

Other Model Evaluation and Interpretation: AutoShapeShap(), CumGainsChart(), EvalPlot(), ParDepCalPlots(), ROCPlot(), RedYellowGreen(), ResidualPlots(), SingleRowShapeShap()

Examples

## Not run: 
data <- data.table::data.table(Target = runif(10))
data[, x1 := qnorm(Target)]
data[, x2 := runif(10)]
data[, Predict := log(pnorm(0.85 * x1 + sqrt(1-0.85^2) * qnorm(x2)))]
data[, ':=' (x1 = NULL, x2 = NULL)]
data <- threshOptim(data     = data,
                    actTar   = "Target",
                    predTar  = "Predict",
                    tpProfit = 0,
                    tnProfit = 0,
                    fpProfit = -1,
                    fnProfit = -2,
                    MinThresh = 0.001,
                    MaxThresh = 0.999,
                    ThresholdPrecision = 0.001)
optimalThreshold <- data$Thresholds
allResults <- data$EvaluationTable

## End(Not run)

AdrianAntico/ModelingTools documentation built on Feb. 1, 2024, 7:33 a.m.