Machine Learning MCQ Questions: Practice and Test Your Knowledge

11

Which of the following statement is true about outliers in Linear regression?

A) Linear regression is sensitive to outliers B) Linear regression is not sensitive to outliers C) Can't say D) None of these

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Answer & Solution

Answer: Option A

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12

Naive Bayes classifiers is . . . . . . . . Learning

A) Supervised B) Unsupervised C) Both D) None

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Answer & Solution

Answer: Option A

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13

The distance between two points calculated using Pythagoras theorem is

A) supremum distance B) eucledian distance C) linear distance D) manhattan distance

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Answer & Solution

Answer: Option B

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14

Features being classified is independent of each other in Nave Bayes Classifier

A) FALSE B) TRUE

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Answer & Solution

Answer: Option B

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15

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.

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Answer & Solution

Answer: Option C

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16

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

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Answer & Solution

Answer: Option A

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17

Suppose your model is demonstrating high variance across the different training sets. Which of the following is NOT valid way to try and reduce the variance?

A) increase the amount of traning data in each traning set B) improve the optimization algorithm being used for error minimization. C) decrease the model complexity D) reduce the noise in the training data

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Answer & Solution

Answer: Option B

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18

The problem of finding hidden structure in unlabeled data is called . . . . . . . .

A) supervised learning B) unsupervised learning C) reinforcement learning D) none of the above

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Answer & Solution

Answer: Option B

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19

what is the function of 'Supervised Learning'?

A) classifications, predict time series, annotate strings B) speech recognition, regression C) both a and b D) none of above

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Answer & Solution

Answer: Option C

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20

Which of the following is true about bagging?
1. Bagging can be parallel
2. The aim of bagging is to reduce bias not variance
3. Bagging helps in reducing overfitting

A) 1 and 2 B) 2 and 3 C) 1 and 3 D) all of these

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Answer & Solution

Answer: Option C

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