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Machine-learning Questions Set 10:

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Which of the following is a common technique for handling imbalanced datasets in SVM?

Sampling

Penalizing

Boosting

Ensemble

Solution:

Which of the following kernel functions is commonly used with SVM for non-linear classification?

Linear

Polynomial

Gaussian

Sigmoid

Solution:

Which of the following is a commonly used optimization algorithm for training SVM?

Stochastic Gradient Descent

Adam

Gradient Descent

Adaboost

Solution:

Which of the following is a method used to handle non-linearly separable data in SVM?

Feature selection

Feature scaling

Kernel trick

Regularization

Solution:

What is the role of support vectors in SVM?

To maximize the margin between classes

To minimize the classification error

To regularize the model

To define the optimal hyperplane

Solution:

In which of the following scenarios would you use a soft-margin SVM?

When the data is linearly separable

When the data is noisy

When the data is imbalanced

When the data is sparse

Solution:

What is the main purpose of the C parameter in SVM?

To control regularization strength

To control the degree of kernel function

To control the margin width

To control the number of support vectors

Solution:

What is the main objective of Support Vector Machines (SVM) algorithm in machine learning?

To minimize false positives

To minimize false negatives

To maximize margin between classes

To minimize the number of support vectors

Solution:

Which of the following is an advantage of using SVM for classification?

It is computationally efficient for large datasets

It performs well with high-dimensional data

It works well with noisy data

It is not affected by imbalanced datasets

Solution:

Which of the following is a limitation of using SVM for multi-class classification?

It requires more computational resources compared to binary classification

It is less accurate than other multi-class classification algorithms

It requires re-training for each new class added to the problem

It cannot handle non-linearly separable data

Solution:

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Machine-learning Questions Set 10:

Which of the following is a common technique for handling imbalanced datasets in SVM?

Solution:

Which of the following kernel functions is commonly used with SVM for non-linear classification?

Solution:

Which of the following is a commonly used optimization algorithm for training SVM?

Solution:

Which of the following is a method used to handle non-linearly separable data in SVM?

Solution:

What is the role of support vectors in SVM?

Solution:

In which of the following scenarios would you use a soft-margin SVM?

Solution:

What is the main purpose of the C parameter in SVM?

Solution:

What is the main objective of Support Vector Machines (SVM) algorithm in machine learning?

Solution:

Which of the following is an advantage of using SVM for classification?

Solution:

Which of the following is a limitation of using SVM for multi-class classification?

Solution:

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