effectiveness_poly {airt} | R Documentation |
Computes the actual and predicted effectiveness of the collection of algorithms.
Description
This function computes the actual and predicted effectiveness of the collection of algorithms for different tolerance values.
Usage
effectiveness_poly(model)
## S3 method for class 'effectivenesspoly'
autoplot(object, plottype = 1, ...)
Arguments
model |
The output of pirtmodel function. |
object |
For autoplot: The output of the function effectiveness_crm |
plottype |
For autoplot: If plottype = 1, then actual effectiveness is plotted, if plottype = 2, then predicted effectiveness is plotted. If plottype = 3, area under the actual effectiveness curve (AUAEC) is plotted against area under the predicted effectiveness curve (AUPEC). |
... |
Other arguments currently ignored. |
Value
A list with the following components:
effectivenessAUC |
The area under the actual and predicted effectiveness curves. |
actcurves |
The |
#'
prdcurves |
The |
Examples
set.seed(1)
x1 <- sample(1:5, 100, replace = TRUE)
x2 <- sample(1:5, 100, replace = TRUE)
x3 <- sample(1:5, 100, replace = TRUE)
X <- cbind.data.frame(x1, x2, x3)
mod <- pirtmodel(X)
out <- effectiveness_poly(mod)
out
# For actual effectiveness curves
autoplot(out, plottype = 1)
# For predicted effectiveness curves
autoplot(out, plottype = 2)
# For Actual and Predicted Effectiveness (AUAEC, AUPEC)
autoplot(out, plottype = 3)