comp.pred

formula

data.train

data.test

string. An algorithm in the set "lr" -- logistic regression, cart" -- decision trees, "rlr" -- regularised logistic regression, "svm" -- support vector machines, "rf" -- random forests

algorithm

model. An optional existing model applied to test data

model

string. What should be done if new factor values are discovered in the test set? "exclude" = exclude (i.e.; remove these cases), "base" = predict the base rate of the criterion.

new.factors

This function is a wrapper for many classification algorithms such as CART (rpart::rpart), logistic regression (glm), support vector machines (svm::svm) and random forests (randomForest::randomForest)

Create, visualize, and test fast-and-frugal decision trees (FFTs). FFTs are very simple decision trees for
binary classification problems. FFTs can be preferable to more complex algorithms because they are easy to communicate, require very little information, and are
robust against overfitting.

comp.pred: Wrapper for classfication algorithms

Description

Usage

Arguments