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- 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)
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