Top 350+ Solved Machine Learning (ML) MCQ Questions Answer
Q. A measurable property or parameter of the data-set is
a. training data
b. feature
c. test data
d. validation data
Q. Suppose that we have N independent variables (X1,X2 Xn) and dependent variable is Y. Now Imagine that you are applying linear regression by fitting the best fit line using least square error on this data. You found that correlation coefficient for one of its variable(Say X1) with Y is -0.95.Which of the following is true for X1?
a. relation between the x1 and y is weak
b. relation between the x1 and y is strong
c. relation between the x1 and y is neutral
d. correlation cant judge the relationship
Q. We have been given a dataset with n records in which we have input attribute as x and output attribute as y. Suppose we use a linear regression method to model this data. To test our linear regressor, we split the data in training set and test set randomly. What do you expect will happen with bias and variance as you increase the size of training data?
a. bias increases and variance increases
b. bias decreases and variance increases
c. bias decreases and variance decreases
d. bias increases and variance decreases
Q. Suppose, you got a situation where you find that your linear regression model is under fitting the data. In such situation which of the following options would you consider?1. I will add more variables2. I will start introducing polynomial degree variables3. I will remove some variables
a. 1 and 2
b. 2 and 3
c. 1 and 3
d. 1, 2 and 3
Q. there's a growing interest in pattern recognition and associative memories whose structure and functioningare similar to what happens in the neocortex. Such an
a. regression
b. accuracy
c. modelfree
d. scalable
Q. showed better performance than other approaches, even without a context-based model
a. machine learning
b. deep learning
c. reinforcement learning
d. supervised learning
Q. Which of the following sentence is correct?
a. machinelearning relates with the study,
b. data miningcan be defined as the process
c. both a & b
d. none of the above
Q. What is ‘Overfitting’ in Machine learning?
a. when astatistical model describes random error or noise instead of
b. robots areprogramed so that they can perform the task based on data they gather from
c. while involving the process of learning ‘overfitting’ occurs.
d. a set of data is used to discover the potentially predictive relationship
Q. What is ‘Test set’?
a. test set is used to test the accuracy of the hypotheses generated by the learner.
b. it is a set of data is used to discover the potentially predictive relationship.
c. both a & b
d. none of above
Q. what is the function of ‘Supervised Learning’?
a. classifications, predict time series, annotate strings
b. speech recognition, regression
c. both a & b
d. none of above
Q. Commons unsupervised applications include
a. objectsegmentation
b. similaritydetection
c. automaticlabeling
d. all above
Q. Reinforcement learning is particularly efficient when .
a. the environment is not completely deterministic
b. it\s often very dynamic
c. it\s impossible to have a precise error measure
d. all above
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 representingthe state.
a. logical
b. classical
c. classification
d. none of above
Q. Common deep learning applications include
a. image classification, real-time visual tracking
b. autonomous car driving, logistic optimization
c. bioinformatics, speech recognition
d. all above