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Classification in Machine Learning2

Total questions: 10

Worksheet time: 7mins

Name
Class
Date
1.

This picture shows a result of ...

a)

Supervised Learning: Classification

b)

Unsupervised Learning: Regression

c)

Unsupervised Learning: Prediction

d)

Supervised Learning: Regression

2.

Machine Learning has various function representation, which of the following is not numerical functions?

a)

Linear Regression

b)

Support Vector Machines

c)

Neural Network

d)

Case-based

3.

All data is labeled and the algorithms learn to predict the output from the input data

a)

Dataset

b)

Classifiers

c)

supervised learning

d)

unsupervised learning

4.

What are the two types of Supervised Learning?

a)

Classification

b)

Declassification

c)

Progression

d)

Regression

5.

You are analyzing a scatter plot that has a negative correlation. What is true for the x and y values?

a)

As x increases, y decreases

b)

As x increases, y increases

c)

As x decreases, y decreases

6.
The scatter plot below shows the number of books read by students in Mrs. Hall’s English class and their final grades. Which statement represents the best description about the line of best fit? 
a)
The more books students read, the lower their English grade.
b)
The more books students read, the higher their English grade.
c)
The fewer books students read, the higher their English grade. 
d)
No relationship exists between the number of books students read and their English grades. 
7.

The faceapp has simulated a person's face based on targetted age. This is example of (Choose best 2 answer)

a)

a classification

b)

a logistic regression classifier

c)

a prediction

d)

great artwork

8.

Which is FALSE about Decision Tree

a)

We can extract RULES from the Decision Tree

b)

It is good to find relationship of non-linearly correlated data

c)

it has to formed from a binary tree

d)

The output can be easily understood by a layman

9.

Logistic regression...

a)

is used to find a continuous value

b)

can be used to predict a house price

c)

Can be used to find the size of a tumor from other parameter

d)

Is used together with clustering

10.

Which of these are associated with SVM?

a)

linear

b)

non-linear

c)

hyperplanes

d)

neighbour

e)

branch