Top 350+ Solved Machine Learning (ML) MCQ Questions Answer
Q. During the last few years, many algorithms have been applied to deepneural networks to learn the best policy for playing Atari video games and to teach an agent how to associate the right action with an input representing the state.
a. logical
b. classical
c. classification
d. none of above
Q. if there is only a discrete number of possible outcomes (called categories),the process becomes a .
a. regression
b. classification.
c. modelfree
d. categories
Q. Let’s say, you are working with categorical feature(s) and you have not looked at the distribution of the categorical variable in the test data.You want to apply one hot encoding (OHE) on the categorical feature(s). What challenges you may face if you have applied OHE on a categorical variable of train dataset?
a. all categories of categorical variable are not present inthe test dataset.
b. frequency distribution of categories is different in train as compared to the test dataset.
c. train and test always have same distribution.
d. both a and b
Q. scikit-learn also provides functions for creating dummy datasets from scratch:
a. make_classifica tion()
b. make_regressio n()
c. make_blobs()
d. all above
Q. which can accept a NumPy RandomState generator or an integer seed.
a. make_blobs
b. random_state
c. test_size
d. training_size
Q. It's possible to specify if the scaling process must include both mean and standard deviation using the parameters .
a. with_mean=tru e/false
b. with_std=true/ false
c. both a & b
d. none of the mentioned
Q. Which of the following selects the best K high-score features.
a. selectpercentil e
b. featurehasher
c. selectkbest
d. all above
Q. What is the purpose of performing cross-validation?
a. To assess the predictive performance of the models
b. b. To judge how the trained model performs outside the sample on test data
Q. Which of the following is true about Naive Bayes ?
a. Assumes that all the features in a dataset are equally important
b. Assumes that all the features in a dataset are independent
c. Both A and B
d. None of the above option
Q. Which of the following is not supervised learning?
a. PCA
b. Decision Tree
c. Naive Bayesian
d. Linerar regression
Q. ______can be adopted when it's necessary to categorize a large amount of data with a few complete examples or when there's the need to impose some constraints to a clustering algorithm.
a. Supervised
b. Semi-supervised
c. Reinforcement
d. Clusters
Q. In reinforcement learning, this feedback is usually called as___.
a. Overfitting
b. Overlearning
c. Reward
d. None of above
Q. In the last decade, many researchers started training bigger and bigger models, built with several different layers that's why this approach is called_____.
a. Deep learning
b. Machine learning
c. Reinforcement learning
d. Unsupervised learning