Tree Validation
In previous section, we studied about Building a Decision Tree in R
- Accuracy=(TP+TN)/(TP+FP+FN+TN)
- Misclassification Rate=(FP+FN)/(TP+FP+FN+TN)
LAB: Tree Validation
- Find the accuracy of the classification for the Ecom_Cust_Survey model
predicted_values<-predict(Ecom_Tree,type="class")
actual_values<-Ecom_Cust_Survey$Overall_Satisfaction
conf_matrix<-table(predicted_values,actual_values)
conf_matrix
## actual_values
## predicted_values Dis Satisfied Satisfied
## Dis Satisfied 6373 652
## Satisfied 38 4749
accuracy<-(conf_matrix[1,1]+conf_matrix[2,2])/(sum(conf_matrix))
accuracy
## [1] 0.9415848
The next post is about The Problem of Over Fitting the Decision Tree.