machine-learning-with-R/Logistic regression Classifier at master · sudheera96/machine-learning-with-R · GitHub

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plot(Social_Network_Ads)
Social_Network_Ads<-Social_Network_Ads[,3:5]

#split the train and test
library(caTools)
split=sample.split(Social_Network_Ads$Purchased,SplitRatio = 0.75)
training_set=subset(Social_Network_Ads,split == TRUE)
testing_set=subset(Social_Network_Ads,split==FALSE)

#feature scaling
training_set[,1:2]=scale(training_set[,1:2])
testing_set[,1:2]=scale(testing_set[,1:2])

#fitting logistic regression
classifier=glm(formula = Purchased~.,family = binomial,data = training_set)


#predict test set
prob_pred=predict(classifier,type = 'response',newdata = testing_set[-3])
y_pred=ifelse(prob_pred>0.5,1,0)

#making the confusion matrix
cm=table(testing_set[,3],y_pred)

[out]:
cm
   y_pred
     0  1
  0 59  5
  1 11 25

# Visualising the Training set results
library(ElemStatLearn)
set = training_set
X1 = seq(min(set[, 1]) - 1, max(set[, 1]) + 1, by = 0.01)
X2 = seq(min(set[, 2]) - 1, max(set[, 2]) + 1, by = 0.01)
grid_set = expand.grid(X1, X2)
colnames(grid_set) = c('Age', 'EstimatedSalary')
prob_set = predict(classifier, type = 'response', newdata = grid_set)
y_grid = ifelse(prob_set > 0.5, 1, 0)
plot(set[, -3],
     main = 'Logistic Regression (Training 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'))

# Visualising the Test set results
library(ElemStatLearn)
set = testing_set
X1 = seq(min(set[, 1]) - 1, max(set[, 1]) + 1, by = 0.01)
X2 = seq(min(set[, 2]) - 1, max(set[, 2]) + 1, by = 0.01)
grid_set = expand.grid(X1, X2)
colnames(grid_set) = c('Age', 'EstimatedSalary')
prob_set = predict(classifier, type = 'response', newdata = grid_set)
y_grid = ifelse(prob_set > 0.5, 1, 0)
plot(set[, -3],
     main = 'Logistic Regression (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'))