suggest_category: Compare model performance by model category from 'caret'...

In modeval: Evaluation of Classification Model Options

Description

suggest_category collects AUC and accuracy results by model category and presents average performance using the model category tags as definded by caret. This helps the user identify the most promising category of models for further exploration.

Usage

suggest_category(addTo, modelTag = NULL)

Arguments

addTo	Summary list that contains model fits to compare.
modelTag	Select model fits containing modelTag in their name.

Value

Plots of AUC and accuracy, organized by category tags.

Examples

## Not run: 
library(mlbench)
data(PimaIndiansDiabetes)
index <- sample(seq_len(nrow(PimaIndiansDiabetes)), 500)
trainingSet <- PimaIndiansDiabetes[index, ]
testSet <- PimaIndiansDiabetes[-index, ]
x <- trainingSet[, -9]
y <- trainingSet[, 9]
x_test <- testSet[, -9]
y_test <- testSet[, 9]
sSummary <- list()
sSummary <- add_model(sSummary, x, y)
sSummary <- add_model(sSummary, x, y, model = c("C5.0Cost", "glmnet"), modelTag = "others")

suggest_category(sSummary)

# vignette("modeval") #check a vignette for further details

## End(Not run)

modeval documentation built on May 29, 2017, 10:54 a.m.