Pasted

rm(list=ls())
library(class)
library(e1071)
library(MLmetrics)
  X1 = c(2, 2, -2, -2, 1, 1, -1, -1)
X2 = c(2, -2, -2, 2, 1, -1, -1, 1)
Y = c(1, 1, 1, 1, 2, 2, 2, 2)
 trainingdata = data.frame(X1,X2,Y)
 X_train = trainingdata[,c("X1","X2")]
Y_train = trainingdata$Y
 X_test = matrix(c(4,5), ncol = 2)
knn(X_train, X_test, Y_train, k = 1)
 X_test = matrix(c(1.8, 4), ncol = 2)
knn(X_train, X_test, Y_train, k = 3, prob = TRUE)
 svm_model = svm(Y ~ ., kernel="radial", type="C-classification", data = trainingdata, gamma = 1)
pred = predict(svm_model, X_train)
Accuracy(pred, Y_train)
 svm_model = svm(Y ~ ., kernel="radial", type="C-classification", data = trainingdata, gamma = 10000000)
X_test = matrix(c(-2, 1.9), ncol = 2)
predict(svm_model, X_test)