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5 Machine Learning Quiz Questions with Answers explanation, Interview
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learning, k-means, elbow method, decision tree, entropy calculation*

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__Machine
learning MCQ - Set 20__

__Machine learning MCQ - Set 20__

1. Which of the following clustering algorithm requires the number of clusters to be pre-specified?

a) hierarchical clustering

**b) k-means clustering**

c) DBSCAN

d) Markov clustering algorithm

**Click here to view answer**

2. Identify the best method that is used for finding optimal clusters in k-means algorithm.

a) Euclidean method

b) Manhattan method

c) Elbow method

d) Silhouette method

**Click here to view answer**

3. We are dealing with samples x where x is a single value. We would like to test two alternative regression models:

1) y = ax + e

2) y = ax + bx^{2}
+ e

Which of these regression models is more appropriate to fit the training data better?

a) model 1

b) model 2

c) both will equally fit

d) not enough data

**Click here to view answer**

4. If we would like to produce learning rules that are easily interpreted by humans, which of the following machine learning task would we use?

a) Logistic regression

b) Nearest neighbor

c) Decision tree learning

d) Support Vector Machine

**Click here to view answer**

5. Following are the target values predicted by a decision tree in a training dataset which we used to find whether a person have passed in interview or not.

[T, T, T, F, F, T, T, T]

What is the entropy H(pass)?

a) –(2/8 log_{2}2/8
+ 6/8 log_{2}6/8)

b) –(2/8 log_{2}2/8
+ 4/8 log_{2}4/8)

c) –(2/6 log_{2}2/6
+ 6/2 log_{2}6/2)

d) 2/8 log_{2}2/8
+ 6/8 log_{2}6/8

**Click here to view answer**

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