GTbasedIM (version 1.0.0)

predictions: Predictions Function: Generate predictions using classifiers from RWeka

Description

This function trains three different classifiers—Random Forest (RF), Support Vector Machine (SVM), and Logistic Regression (LR)—on the input dataset and returns their predictions.

Usage

predictions(Xdata, Ydata)

Value

A list containing predictions from the three models:

predictionRF

Predictions from the Random Forest (RF) model.

predictionSVM

Predictions from the Support Vector Machine (SVM) model.

predictionLR

Predictions from the Logistic Regression (LR) model.

Arguments

Xdata

Matrix. A dataset where rows represent observations and columns represent features.

Ydata

Vector. The actual response variable associated with each row in Xdata.

Details

The function utilizes the RWeka package to build three different classifiers: Random Forest (RF), Support Vector Machine (SVM), and Logistic Regression (LR). It then predicts the response variable for the input data using each of these models.

References

Davila-Pena, L., Saavedra-Nieves, A., & Casas-Méndez, B. (2024). On the influence of dependent features in classification problems: a game-theoretic perspective. arXiv preprint. tools:::Rd_expr_doi("10.48550/arXiv.2408.02481").

Examples

# Example usage:

X <- matrix(rnorm(100), ncol=5)
Y <- sample(0:1, 20, replace=TRUE)
predictions(X, Y)