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ML Course Activity-II

Total questions: 10

Worksheet time: 10mins

Name
Class
Date
1.

_______ is basically a type of unsupervised learning method.

a)

Un-supervised Learning

b)

Clustering

c)

Supervised Learning

d)

All

2.

_____ in which we will fit the data on the probability that how it may belong to the same distribution

a)

Centroid-based methods                              

b)

Connectivity-based methods

c)

Distribution-based model

d)

All

3.

__________clusters formed in this method form a tree-type structure based on the hierarchy.       

a)

Density-Based                                            

b)

Image-Based

c)

Grid-based                                                  

d)

Hierarchical Based

4.

__________consider the clusters as the dense region having some similarities and differences from the lower dense region of the space.  

a)

Density-Based 

b)

Hierarchical Based

c)

Grid-based                   

d)

None of these

5.

Choose from the following that is Decision Tree nodes.                                                                   

a)

Decision Nodes                                           

b)

End Nodes

c)

Chance Nodes                                            

d)

All of the mentioned

6.

What is Decision Tree?

a)

Flow-Chart & Structure in which the internal node represents a test on an attribute, each branch represents the outcome of the test and each leaf node represents the class label

b)

Structure in which the internal node represents a test on an attribute, each branch represents the outcome of the test and each leaf node represents a class label

c)

Flow-Chart

d)

All the above

7.

Decision makers who are concerned with tactical (short-term) operational problems and decision making is  

a)

Executive managers

b)

Mobile managers 

c)

Middle managers

d)

Supervisors    

8.

If you use an ensemble of different base models, is it necessary to tune the hyperparameters of all base models to improve the ensemble performance?   

a)

Yes

b)

No

c)

Can't say

d)

None

9.

Generally, an ensemble method works better, if the individual base models have ____________

a)

Correlation does not have any impact on ensemble output

b)

Less correlation among predictions

c)

High correlation among predictions 

d)

All the above

10.

Which of the following algorithm is not an example of an ensemble method? 

a)

Gradient Boosting

b)

Extra Tree Regressor    

c)

Random Forest

d)

Decision Tree