Support Vector Machines: Linear vs Non-linear Classes Quiz

What does an Inner Product measure?

Similarity of two observations using standard correlation

What does a Kernel quantify?

Similarity of two points

What happens when the degree in a polynomial kernel is set to 1?

SVMFit reduces to the support vector classifier

Which type of kernel operates in infinite dimensions?

Radial Kernel Signup and view all the answers

What is the purpose of a Support Vector Classifier with Non-Linear Kernels?

Transform lower dimension data into higher dimension space Signup and view all the answers

What does < Vector D1 , Vector D2 > represent?

| D1 | * | D2 | * cos(θ) Signup and view all the answers

In SVM, what does a larger gamma parameter value imply for the radial kernel?

Smaller kernel Signup and view all the answers

What is the effect of having a smaller cost parameter in SVM?

Wider kernel Signup and view all the answers

How does SVM handle the process of tuning hyperparameters?

Through the tune() function Signup and view all the answers

What does a positive value of the cost parameter in SVM indicate?

Higher complexity Signup and view all the answers

How does SVM approach the classification task with the radial kernel?

By minimizing misclassifications Signup and view all the answers

What is a key role of the gamma parameter in SVM with the radial kernel?

Adjusting class boundaries Signup and view all the answers

What is the main limitation of the Support Vector Classifier (SVC) according to the text?

It is only suitable for linearly separable classes Signup and view all the answers

How can the limitations of the Support Vector Classifier (SVC) be addressed?

By transforming data into a higher dimension space using kernels Signup and view all the answers

What is the purpose of transforming lower dimension data into a higher dimension space in Support Vector Machine (SVM)?

To increase the feature space for better separation Signup and view all the answers

Why is Linear SVC considered inadequate for dealing with Mortgage $ and Age features?

Mortgage $ and Age are not linearly separable Signup and view all the answers

What does Support Vector Machine (SVM) do to handle non-linear classes?

It enlarges the feature space using kernels Signup and view all the answers

Why is it necessary to enlarge the feature space in Support Vector Machine (SVM)?

To enable better separation of classes Signup and view all the answers