Machine Learning MCQ Questions: Practice and Test Your Knowledge

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Each section contains 100 MCQs on Machine Learning .

Lasso can be interpreted as least-squares linear regression where

A) weights are regularized with the l1 norm B) the weights have a gaussian prior C) weights are regularized with the l2 norm D) the solution algorithm is simpler

Discuss

Answer & Solution

Answer: Option A

No explanation is given for this question. Let's Discuss on Board

Which of the following method is used to find the optimal features for cluster analysis

A) k-means B) density-based spatial clustering C) spectral clustering find clusters D) all above

Discuss

Answer & Solution

Answer: Option D

No explanation is given for this question. Let's Discuss on Board

Perceptron Classifier is

A) unsupervised learning algorithm B) semi-supervised learning algorithm C) supervised learning algorithm D) soft margin classifier

Discuss

Answer & Solution

Answer: Option C

No explanation is given for this question. Let's Discuss on Board

The correlation coefficient for two real-valued attributes is -0.85. What does this value tell you?

A) the attributes are not linearly related. B) as the value of one attribute increases the value of the second attribute also increases C) as the value of one attribute decreases the value of the second attribute increases D) the attributes show a linear relationship

Discuss

Answer & Solution

Answer: Option C

No explanation is given for this question. Let's Discuss on Board

There are also many univariate methods that can be used in order to select the best features according to specific criteria based on . . . . . . . .

A) F-tests and p-values B) chi-square C) ANOVA D) All above

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Answer & Solution

Answer: Option A

No explanation is given for this question. Let's Discuss on Board

Which of the following is an application of NN (Neural Network)?

A) sales forecasting B) data validation C) risk management D) all of the mentioned

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Answer & Solution

Answer: Option D

No explanation is given for this question. Let's Discuss on Board

Which statement is true about the K-Means algorithm?

A) the output attribute must be cateogrical B) all attribute values must be categorical C) all attributes must be numeric D) attribute values may be either categorical or numeric

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Answer & Solution

Answer: Option C

No explanation is given for this question. Let's Discuss on Board

which of the following step / assumption in regression modeling impacts the trade-off between under-fitting and over-fitting the most.

A) The polynomial degree B) Whether we learn the weights by matrix inversion or gradient descent C) The use of a constant-term D) None of these

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Answer & Solution

Answer: Option A

No explanation is given for this question. Let's Discuss on Board

How can we best represent 'support' for the following association rule: "If X and Y, then Z".

A) $$\frac{{{\text{x}},{\text{y}}}}{{{\text{total number of transactions}}}}$$ B) $$\frac{z}{{{\text{total number of transactions}}}}$$ C) $$\frac{z}{{{\text{x,y}}}}$$ D) $$\frac{{{\text{x}},{\text{y,}}\,{\text{z}}}}{{{\text{total number of transactions}}}}$$

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Answer & Solution

Answer: Option C

No explanation is given for this question. Let's Discuss on Board

With Bayes theorem the probability of hypothesis(H) specified by P(H) is referred to as

A) a conditional probability B) an a priori probability C) a bidirectional probability D) a posterior probability

Discuss

Answer & Solution

Answer: Option B

No explanation is given for this question. Let's Discuss on Board

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