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)