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ML-Set2.5

Authored by deepika ponnusamy

Computers

University

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ML-Set2.5
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15 questions

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1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following is not a type of Machine Learning?

a) Supervised Learning

b) Unsupervised Learning

c) Reinforcement Learning

d) Analytical Learning

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following is a common application of Supervised Learning?

a) Image Classification

b) Clustering

c) Anomaly Detection

d) Dimensionality Reduction

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the primary goal of Reinforcement Learning?

d) To reduce the number of features in a dataset

c) To group similar data points

b) To learn a policy that maximizes cumulative reward

a) To predict outcomes based on input data

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Which of the following techniques is typically used in Unsupervised Learning?

d) Linear Regression

a) Decision Trees

b) K-Means Clustering

c) Support Vector Machines

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

A random variable is a function that maps outcomes of a random process to:

a) Probabilities

b) Real numbers

c) Events

d) Frequencies

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the main difference between Supervised Learning and Unsupervised Learning?

b) Unsupervised Learning is faster than Supervised Learning

a) Supervised Learning uses labeled data, while Unsupervised Learning does not

c) Supervised Learning is only used for classification tasks

d) Unsupervised Learning requires more data than Supervised Learning

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

In the context of Machine Learning, what does 'overfitting' refer to?

d) A model that uses too many features

c) A model that is too simple to capture the underlying patterns

b) A model that generalizes well to new data

a) A model that performs well on training data but poorly on unseen data

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