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The '''`confusionMatrix`''' function prepares the confusion matrix for a prediction, such as that from an [[R/XGBoost|XGBoost]] model using the option objective = "binary:logistic" The '''`confusionMatrix`''' function prepares the confusion matrix for a prediction, such as that from an [[R/XGBoost|XGBoost]] model.

R caret

caret (Classification And REgression Training) is a library of functions for model training.

Contents

  1. R caret
    1. Installation
    2. Usage

Installation

install.packages('caret')

Usage

The createDataPartition function randomly partitions a vector of outcomes. 

data(mtcars)

parts = createDataPartition(mtcars$mpg, p = .8)
train = mtcars[parts, ]
test = mtcars[-parts, ]

createDataPartition returns a list object. To instead return a matrix, pass list = FALSE as an option.

The confusionMatrix function prepares the confusion matrix for a prediction, such as that from an XGBoost model. 

my.data <- xgb.DMatrix(data = df[,predictors], label=df$outcome)
my.model <- xgboost(data = my.data, objective = "binary:logistic", ...)
pred <- predict(my.model, my.data)
pred <- ifelse(pred > 0.5, 1, 0)

confusionMatrix(as.factor(pred), as.factor(df$outcome))

CategoryRicottone

R/Caret (last edited 2025-03-20 15:05:45 by DominicRicottone)