Machine Learning: Classifier Decision Boundary
An R script which plots the decision boundaries of the machine learning algorithms.
Algorithms and parameters
- K Nearest Neighbors (KNN) for k = {1, 3, 5, 10, 30}
- Support Vector Machine (SVM) for kernels = {linear, polynomial, radial, sigmoid}
- Naive Bayes
- Tree-based:
- C.50, CART and Random Forest
- Artificial Neural Network (ANN) for neurons = {1, 10, 100, 500, 1000}
- Artificial Neural Network (ANN) for max_iterations = {10, 100, 500, 1000, 10000}
Datasets
The algorithms above are applied to a collection of artificial datasets (machine learning benchmark problems), available on the package 'mlbench'.
Packages
This script will make use of the following packages:
- C50
- caret
- e1071
- ggplot2
- grid
- gridExtra
- mlbench
- mlogit
- neuralnet
- nnet
- randomForest
- rpart
There is no need to manually pre-install the packages, as there is a function (check below) which checks if you already have the package, otherwise it intalls during the first run.
install_packages <- function(packs) {
for (pack in packs){
if (!pack %in% installed.packages()) install.packages(pack)
}
}
install_packages(packs=c("ggplot2","grid","gridExtra","mlbench","caret","e1071",
"C50","rpart","randomForest","nnet","neuralnet","mlogit"))
Authors
- Adriano Henrique Cantão - ahCantao
- José Augusto Baranauskas