Top 350+ Solved Machine Learning (ML) MCQ Questions Answer
Q. Suppose you are using RBF kernel in SVM with high Gamma value. What does this signify?
a. The model would consider even far away points from hyperplane for modeling
b. The model would consider only the points close to the hyperplane for modeling
c. The model would not be affected by distance of points from hyperplane for modeling
d. None of the above
Q. Which statement about outliers is true?
a. outliers should be part of the training dataset but should not be present in the test data
b. outliers should be identified and removed from a dataset
c. the nature of the problem determines how outliers are used
d. outliers should be part of the test dataset but should not be present in the training data
Q. If TP=9 FP=6 FN=26 TN=70 then Error rate will be
a. 45 percentage
b. 99 percentage
c. 28 percentage
d. 20 perentage
Q. he minimum time complexity for training an SVM is O(n2). According to this fact, what sizes of datasets are not best suited for SVM’s?
a. large datasets
b. small datasets
c. medium sized datasets
d. size does not matter
Q. Perceptron Classifier is
a. unsupervised learning algorithm
b. semi-supervised learning algorithm
c. supervised learning algorithm
d. soft margin classifier
Q. Type of dataset available in Supervised Learning is
a. unlabeled dataset
b. labeled dataset
c. csv file
d. excel file
Q. which among the following is the most appropriate kernel that can be used with SVM to separate the classes.
a. linear kernel
b. gaussian rbf kernel
c. polynomial kernel
d. option 1 and option 3
Q. The SVMs are less effective when
a. the data is linearly separable
b. the data is clean and ready to use
c. the data is noisy and contains overlapping points
d. option 1 and option 2
Q. Suppose you are using RBF kernel in SVM with high Gamma value. What does this signify?
a. the model would consider even far away points from hyperplane for modeling
b. the model would consider only the points close to the hyperplane for modeling
c. the model would not be affected by distance of points from hyperplane for modeling
d. opton 1 and option 2
Q. What is the precision value for following confusion matrix of binary classification?
a. 0.91
b. 0.09
c. 0.9
d. 0.95
Q. Which of the following are components of generalization Error?
a. bias
b. vaiance
c. both of them
d. none of them
Q. Which of the following is not a kernel method in SVM?
a. linear kernel
b. polynomial kernel
c. rbf kernel
d. nonlinear kernel