Jobs By Abekus

Machine-learning Questions Set 11:

Quiz Mode

Which of the following is a commonly used kernel function in SVM?

ReLU

Softmax

ELU

Sigmoid

Solution:

Which of the following is a hyperparameter in SVM?

Bias

Intercept

Weights

Regularization Parameter

Solution:

Which of the following is a hyperparameter in SVM that controls the spread of the RBF kernel?

Gamma

Degree

Coefficient

Solution:

Which of the following is a technique used to select the optimal hyperparameters in SVM?

Random search

Grid search

Gradient descent

Evolutionary algorithms

Solution:

Which of the following is an approach used to handle imbalanced datasets in SVM?

Over-sampling the minority class

Under-sampling the majority class

Cost-sensitive learning

Ensemble learning

Solution:

Which of the following is true about the decision boundary in SVM?

It always passes through the origin

It is perpendicular to the support vectors

It is a straight line in linear SVM

It is determined by the kernel function

Solution:

Which of the following is a disadvantage of using SVM for classification?

It is not suitable for large datasets

It is sensitive to the choice of kernel function

It cannot handle imbalanced datasets

It is prone to overfitting with small datasets

Solution:

Which of the following is a disadvantage of using the RBF kernel in SVM?

It is computationally efficient for large datasets

It may lead to overfitting with small datasets

It cannot handle non-linearly separable data

It is not suitable for noisy data

Solution:

Which of the following is true about the support vectors in SVM?

They are the data points that are closest to the decision boundary

They are the data points that are furthest from the decision boundary

They are the data points that have non-zero coefficients in the SVM solution

They are the data points that are misclassified by the SVM

Solution:

Which of the following is a disadvantage of using a radial basis function (RBF) kernel in SVM?

It is less computationally efficient than other kernel functions

It is more prone to overfitting with small datasets

It is not suitable for non-linearly separable data

It requires more tuning of hyperparameters compared to other kernel functions

Solution:

Scroll to Top

Company

About Us Our Values Mission Approach Abekus Family Careers Privacy Policy Terms & Conditions Cancellation & Refunds Job Guidelines Shipping and Exchanges

Product

Resume Builder Blog Jobs for Recruiters Abekus (Learning)AI Resume Analysis Bulk Resume Analyser

Get in touch

Social Network:

Machine-learning Questions Set 11:

Which of the following is a commonly used kernel function in SVM?

Solution:

Which of the following is a hyperparameter in SVM?

Solution:

Which of the following is a hyperparameter in SVM that controls the spread of the RBF kernel?

Solution:

Which of the following is a technique used to select the optimal hyperparameters in SVM?

Solution:

Which of the following is an approach used to handle imbalanced datasets in SVM?

Solution:

Which of the following is true about the decision boundary in SVM?

Solution:

Which of the following is a disadvantage of using SVM for classification?

Solution:

Which of the following is a disadvantage of using the RBF kernel in SVM?

Solution:

Which of the following is true about the support vectors in SVM?

Solution:

Which of the following is a disadvantage of using a radial basis function (RBF) kernel in SVM?

Solution:

Related Question Sets:

Related Topics: