Machine Learning, Support Vector Machine, Support Vector Classifier, Data Scie, Svm.
print(accuracy_score(y_test, y_pred_1)) sns.heatmap(cm, annot=True, cmap='Blues') We got the accuracy score of 0.95 which is great and the following confusion matrix: Only one observation is not predicted correctly. Bravo! How to tune it To tune it you can play around with two hyperparameters: C: