Machine Learning and its Applications

Machine Learning and its Applications

University

15 Qs

quiz-placeholder

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Machine Learning and its Applications

Machine Learning and its Applications

Assessment

Quiz

Computers

University

Hard

Created by

Dr. Raikwar

Used 61+ times

FREE Resource

15 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

You are given reviews of movies marked as positive, negative, and neutral. Classifying reviews of a new movie is an example of

Supervised Learning

Unsupervised Learning

Reinforcement Learning

None of these

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

The selling price of a house depends on many factors. For example, it depends on

the number of bedrooms, number of kitchen, number of bathrooms, the year the house was

built, and the square footage of the lot. Given these factors, predicting the selling price of

the house is an example of ____________ task.

Binary Classification

Multilabel Classification

Simple Linear Regression

Multiple Linear Regression

3.

MULTIPLE CHOICE QUESTION

1 min • 1 pt

Regarding bias and variance, which of the following statements are true? (Here ‘high’ and ‘low’ are relative to the ideal model.)


(i). Models which overfit are more likely to have high bias

(ii). Models which overfit are more likely to have low bias

(iii). Models which overfit are more likely to have high variance

(iv). Models which overfit are more likely to have low variance

(i) and (ii)

(ii) and (iii)

(iii) and (iv)

None of these

4.

MULTIPLE CHOICE QUESTION

1 min • 1 pt

State whether the statements are True or False.


Statement A: When the hypothesis space is richer, overfitting is more likely.


Statement B: When the feature space is larger, overfitting is more likely.

False, False

True, False

True, True

False, True

5.

MULTIPLE CHOICE QUESTION

1 min • 1 pt

What is the purpose of restricting hypothesis space in machine learning?

Can be easier to search

May avoid overfit since they are usually simpler (e.g. linear or low order decision surface)

Both of the above

None of the above

6.

MULTIPLE SELECT QUESTION

1 min • 1 pt

Suppose, you got a situation where you find that your linear regression model is under fitting the data. In such situation which of the following options would you consider?

You will add more features

You will start introducing higher degree features

You will remove some features

None of the above.

7.

MULTIPLE CHOICE QUESTION

1 min • 1 pt

Consider a simple linear regression model with one independent variable (X). The output variable is Y. The equation is : Y=aX+b, where a is the slope and b is the intercept. If we change the input variable (X) by 1 unit, by how much output variable (Y) will change?

1 unit

By slope

By intercept

None

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