Top 350+ Solved Machine Learning (ML) MCQ Questions Answer
Q. Application of machine learning methods to large databases is called
a. data mining.
b. artificial intelligence
c. big data computing
d. internet of things
Q. If machine learning model output involves target variable then that model is called as
a. descriptive model
b. predictive model
c. reinforcement learning
d. all of the above
Q. In what type of learning labelled training data is used
a. unsupervised learning
b. supervised learning
c. reinforcement learning
d. active learning
Q. In following type of feature selection method we start with empty feature set
a. forward feature selection
b. backword feature selection
c. both a and b??
d. none of the above
Q. Suppose you are given ‘n’ predictions on test data by ‘n’ different models (M1, M2, …. Mn) respectively. Which of the following method(s) can be used to combine the predictions of these models?Note: We are working on a regression problem1. Median2. Product3. Average4. Weighted sum5. Minimum and Maximum6. Generalized mean rule
a. 1, 3 and 4
b. 1,3 and 6
c. 1,3, 4 and 6
d. all of above
Q. In an election, N candidates are competing against each other and people are voting for either of the candidates. Voters don’t communicate with each other while casting their votes. Which of the following ensemble method works similar to above-discussed election procedure?Hint: Persons are like base models of ensemble method.
a. bagging
b. 1,3 and 6
c. a or b
d. none of these
Q. A feature F1 can take certain value: A, B, C, D, E, & F and represents grade of students from a college.Which of the following statement is true in following case?
a. feature f1 is an example of nominal variable.
b. feature f1 is an example of ordinal variable.
c. it doesnt belong to any of the above category.
d. both of these
Q. What would you do in PCA to get the same projection as SVD?
a. transform data to zero mean
b. transform data to zero median
c. not possible
d. none of these
Q. What is PCA, KPCA and ICA used for?
a. principal components analysis
b. kernel based principal component analysis
c. independent component analysis
d. all above
Q. Features being classified is of each other in Nave Bayes Classifier
a. independent
b. dependent
c. partial dependent
d. none
Q. What does learning exactly mean?
a. robots are programed so that they can perform the task based on data they gather from sensors.
b. a set of data is used to discover the potentially predictive relationship.
c. learning is the ability to change according to external stimuli and remembering most of all previous experiences.
d. it is a set of data is used to discover the potentially predictive relationship.
Q. When it is necessary to allow the model to develop a generalization ability and avoid a common problem called .
a. overfitting
b. overlearning
c. classification
d. regression
Q. Techniques involve the usage of both labeled and unlabeled data is called .
a. supervised
b. semi-supervised
c. unsupervised
d. none of the above
Q. In reinforcement learning if feedback is negative one it is defined as .
a. penalty
b. overlearning
c. reward
d. none of above
Q. A supervised scenario is characterized by the concept of a .
a. programmer
b. teacher
c. author
d. farmer