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[azhangbojun]

Hello, I am using ElemStatLearn very well now, but I still want to try some different things, so here is my code for making a Kernel SVM and its plot.

# Importing the dataset
dataset = read.csv('Social_Network_Ads.csv')
dataset = dataset[3:5]
dataset$Purchased = factor(dataset$Purchased,levels=c(0,1))

# Splitting the dataset into the Training set and Test set
# install.packages('caTools')

library(caTools)
set.seed(123)
split = sample.split(dataset$Purchased, SplitRatio = 0.75)
training_set = subset(dataset, split == TRUE)
test_set = subset(dataset, split == FALSE)

#Feature Scaling
training_set[-3] = scale(training_set[-3])
test_set[-3] = scale(test_set[-3])

# Fitting Simple Linear Regression to the Training set
library(e1071)
classifier = svm(formula= Purchased~.,
                 data= training_set,
                 type='C-classification',
                 kernel = 'radial') 


# Predicting the Test set results
y_pred = predict(classifier, newdata = test_set)
y_pred

cm = table(test_set[,3],y_pred)
cm


# Visualising the Training set results

#tranining set
library(ElemStatLearn)
set = training_set
X1 = seq(min(set[, 1]) - 1, max(set[, 1]) + 1, by = 0.0075)
X2 = seq(min(set[, 2]) - 1, max(set[, 2]) + 1, by = 0.0075)
grid_set = expand.grid(X1, X2)
colnames(grid_set) = c('Age', 'EstimatedSalary')
y_grid = predict(classifier, newdata = grid_set)
plot(set[, -3], main = 'Classifier (Tranining set)',
     xlab = 'Age', ylab = 'Estimated Salary',
     xlim = range(X1), ylim = range(X2))
contour(X1, X2, matrix(as.numeric(y_grid), length(X1), length(X2)), add = TRUE)
points(grid_set, pch = '.', col = ifelse(y_grid == 1, 'springgreen3', 'tomato'))
points(set, pch = 21, bg = ifelse(set[, 3] == 1, 'green4', 'red3'))
#test set
library(ElemStatLearn)
set = test_set
X1 = seq(min(set[, 1]) - 1, max(set[, 1]) + 1, by = 0.0075)
X2 = seq(min(set[, 2]) - 1, max(set[, 2]) + 1, by = 0.0075)
grid_set = expand.grid(X1, X2)
colnames(grid_set) = c('Age', 'EstimatedSalary')
y_grid = predict(classifier, newdata = grid_set)
plot(set[, -3], main = 'Classifier (Test set)',
     xlab = 'Age', ylab = 'Estimated Salary',
     xlim = range(X1), ylim = range(X2))
contour(X1, X2, matrix(as.numeric(y_grid), length(X1), length(X2)), add = TRUE)
points(grid_set, pch = '.', col = ifelse(y_grid == 1, 'springgreen3', 'tomato'))
points(set, pch = 21, bg = ifelse(set[, 3] == 1, 'green4', 'red3'))

Here is the data link:
https://sds-platform-private.s3-us-east-2.amazonaws.com/uploads/P46-Section12-Kernel-SVM.zip

So in the last part is I am using ElemStatLearn and this code running well.
I tried to think over all things and I found the logic is a little different that ElemStatLearn is making every dots in this plot and ggplot is making a line in this plot. But is it possible to use other packages or ggplot to make it?