Support Vector Machine-Classification: We have already understood conceptually, how Support Vector Machine algorithm works. Let’s try to implement a SVM logic using Python commands.
We would use Loan Default data to implement SVM- Classification.
Step 1: Import the Libraries. We would use three libraries for this analysis:
Use below command to import the libraries.
Step 2: Import the data set.
Step 3: Splitting the data set into the Training set and Test set. Provided data set has 300 observations, we would divide it into 75%-25% for training and testing purpose.
Step 4: Feature Scaling: Since range of two of our predictor variables is very different, while Age varies from 18-60 whereas salary varies from 1127-142293. We need to do feature scaling so that both of the variables have same proportional impact on the target variable. In the following command we are excluding the target variable from feature scaling which is at position 3.
Step 5: Fitting SVM to the Training set
Step 6: Predicting the Test set results
Step 7: Making the Confusion Matrix