To examine classification for k-fold cross-validation and naïve Bayes, two packages contain the necessary functions for partitioning the data. These are
A) caret & klaR
B) caret & Crisp
C) klarR & SEMMA
D) predictive & caret

Question

Quizplus · Accepted Answer

The caret package in R is a comprehensive framework for building machine learning models, which includes functions for data splitting, pre-processing, feature selection, model tuning using resampling, variable importance estimation, as well as tools for visualizing and comparing models. It supports k-fold cross-validation among other techniques. The klaR package provides functionality for classification and visualization, including Naïve Bayes classifiers, making it a suitable companion for tasks involving Naïve Bayes classification. Together, caret and klaR offer a robust set of tools for handling both k-fold cross-validation and Naïve Bayes classification tasks.

To Examine Classification for K-Fold Cross-Validation and Naïve Bayes, Two