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Frequently Asked Questions

What is SVM classifier?

That's why an SVM classifier is also known as a discriminative classifier. SVM finds an optimal hyperplane which helps in classifying new data points. How does it work? Generally, Support Vector Machines is considered to be a classification approach, it but can be employed in both types of classification and regression problems.

How to import SVM model from sklearn?

#Import svm model from sklearn import svm #Create a svm Classifier clf = svm. SVC ( kernel ='linear') # Linear Kernel #Train the model using the training sets clf. fit ( X_train, y_train) #Predict the response for test dataset y_pred = clf. predict ( X_test)

How to import scikit-learn dataset library from sklearn?

#Import scikit-learn dataset library from sklearn import datasets #Load dataset cancer = datasets. load_breast_cancer () After you have loaded the dataset, you might want to know a little bit more about it. You can check feature and target names.

What is a good margin in SVM?

A margin is a gap between the two lines on the closest class points. This is calculated as the perpendicular distance from the line to support vectors or closest points. If the margin is larger in between the classes, then it is considered a good margin, a smaller margin is a bad margin. How does SVM work?


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