Top 350+ Solved Machine Learning (ML) MCQ Questions Answer
Q. overlearning causes due to an excessive ______.
a. Capacity
b. Regression
c. Reinforcement
d. Accuracy
Q. Which of the following statements about Naive Bayes is incorrect?
a. A. Attributes are equally important.
b. Attributes are statistically dependent of one another given the class value.
c. C. Attributes are statistically independent of one another given the class value.
d. D. Attributes can be nominal or numeric
Q. In multiclass classification number of classes must be
a. less than two
b. equals to two
c. greater than two
d. option 1 and option 2
Q. Which of the following can only be used when training data are linearlyseparable?
a. linear hard-margin svm
b. linear logistic regression
c. linear soft margin svm
d. the centroid method
Q. Impact of high variance on the training set ?
a. overfitting
b. underfitting
c. both underfitting & overfitting
d. depents upon the dataset
Q. What do you mean by a hard margin?
a. the svm allows very low error in classification
b. the svm allows high amount of error in classification
c. both 1 & 2
d. none of the above
Q. The effectiveness of an SVM depends upon:
a. selection of kernel
b. kernel parameters
c. soft margin parameter c
d. all of the above
Q. What are support vectors?
a. all the examples that have a non-zero weight ??k in a svm
b. the only examples necessary to compute f(x) in an svm.
c. all of the above
d. none of the above
Q. A perceptron adds up all the weighted inputs it receives, and if it exceeds a certain value, it outputs a 1, otherwise it just outputs a 0.
a. true
b. false
c. sometimes – it can also output intermediate values as well
d. can’t say
Q. What is the purpose of the Kernel Trick?
a. to transform the data from nonlinearly separable to linearly separable
b. to transform the problem from regression to classification
c. to transform the problem from supervised to unsupervised learning.
d. all of the above
Q. Which of the following can only be used when training data are linearlyseparable?
a. linear hard-margin svm
b. linear logistic regression
c. linear soft margin svm
d. parzen windows
Q. The firing rate of a neuron
a. determines how strongly the dendrites of theneuron stimulate axons of neighboring neurons
b. is more analogous to the output of a unit in aneural net than the output voltage of the neuron
c. only changes very slowly, taking a period ofseveral seconds to make large adjustments
d. can sometimes exceed 30,000 action potentialsper second
Q. Which of the following evaluation metrics can not be applied in case of logistic regression output to compare with target?
a. auc-roc
b. accuracy
c. logloss
d. mean-squared-error
Q. The cost parameter in the SVM means:
a. the number of cross-validations to be made
b. the kernel to be used
c. the tradeoff between misclassification and simplicity of the model
d. none of the above
Q. The kernel trick
a. can be applied to every classification algorithm
b. is commonly used for dimensionality reduction
c. changes ridge regression so we solve a d ?? dlinear system instead of an n ?? n system, given nsample points with d features
d. exploits the fact that in many learning algorithms, the weights can be written as a linearcombination of input points