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ML-Basics

Total questions: 25

Worksheet time: 13mins

Name
Class
Date
1.

In K-NN, is the query time longer than the training time?

a)

Yes

b)

No

2.

Which of the following options is true about the k-NN algorithm?

a)

It can be used for classification

b)

It can be used for regression

c)

It can be used for both classification and regression

3.

Which of the following is true about Manhattan distances?

a)

It can be used for continuous variables

b)

It can be used for categorical variables

c)

It can be used for categorical as well as continuous variables

4.

In the image below, which would be the best value for k assuming that the algorithm you are using is k-Nearest Neighbor.

a)

3

b)

10

c)

20

d)

50

5.

Locally Weighted Regression is

a)

parametric Approach

b)

Non- parametric Approach

c)

None of Them

6.

Locally weighted regression is used for

a)

classification

b)

Regression

c)

Both classification and regression

d)

None

7.

Locally Weighted Regression is a

a)

Lazy learning method

b)

Eager Learning Method

c)

Both

d)

None

8.

Locally Weighted Regression is a

a)

Lazy learning method

b)

Eager Learning Method

c)

Both

d)

None

9.

Most of the computation is performed in which phase?

a)

Training Phase

b)

testing Phase

c)

bothe

d)

validation phase

10.

from the picture, what kind of programming is it?

a)

Traditional Programming

b)

Modern Programming

c)

Machine Learning

d)

Traditional Learning

11.

from the picture, what kind of programming is it?

a)

Traditional Programming

b)

Machine Learning

c)

Modern Programming

d)

Traditional Learning

12.

What kind of learning algorithm for "Future stock prices or currency exchange rates"?

a)

Recognizing Anomalies

b)

Prediction

c)

Generating Patterns

d)

Recognition Patterns

13.

Which of the following is not type of learning?

a)

Semi-unsupervised Learning

b)

Unsupervised Learning

c)

Supervised Learning

d)

Reinforcement Learning

14.

Targetted marketing, Recommended Systems, and Customer Segmentation are applications in ...

a)

Unsupervised Learning: Clustering

b)

Supervised Learning: Classification

c)

Reinforcement Learning

d)

Unsupervised Learning: Regression

15.

Real-Time decisions, Game AI, Learning Tasks, Skill Aquisition, and Robot Navigation are applications in ...

a)

Unsupervised Learning: Clustering

b)

Supervised Learning: Classification

c)

Reinforcement Learning

d)

Unsupervised Learning: Regression

16.

Fraud Detection, Image Classification, Diagnostic, and Customer Retention are applications in ...

a)

Unsupervised Learning: Clustering

b)

Supervised Learning: Classification

c)

Reinforcement Learning

d)

Unsupervised Learning: Regression

17.

In k-mean algorithm, K stands for

a)

Number of data

b)

Number of clusters

c)

Number of attributes

d)

Number of iterations

18.

A group of baking videos on youtube

a)

Cluster

b)

Class

c)

Regression

19.

Estimate the price of a house

a)

Cluster

b)

Class

c)

Regression

20.

Identifying a man

a)

Cluster

b)

Class

c)

Regression

21.

The price of a smartphone

a)

Cluster

b)

Class

c)

Regression

22.

Students Grades vs Attendance

a)

Cluster

b)

Class

c)

Regression

23.

Text Recognition

a)

Class

b)

Cluster

c)

Regression

24.

Group different cats based on their looks

a)

Cluster

b)

Class

c)

Regression

25.

Weather forecast

a)

Cluster

b)

Class

c)

Regression