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K-NN algorithm for machine learning

Authored by ammar AlDallal

Computers

University

Used 1+ times

K-NN algorithm for machine learning
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10 questions

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1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is kNN?

A clustering algorithm

A reinforcement learning algorithm

A supervised learning algorithm

An unsupervised learning algorithm

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How does kNN classify new examples?

By finding the most dissimilar training examples

By choosing the k closest neighbors

By ignoring all training examples

Based on random selection

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the purpose of scaling in kNN?

To reduce the number of attributes

To remove irrelevant attributes

To make the data more complex

To normalize the variables to the same scale

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the distance formula used in kNN?

Cosine Similarity

Chebyshev Distance

Minkowski Distance

Manhattan Distance

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How does kNN handle noise in labels?

By assigning a random label

By increasing the value of k

By choosing the most frequent label of its k nearest neighbors

By discarding the noisy examples

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is an advantage of kNN?

Only suitable for regression problems

Performs poorly with large datasets

Simple to implement algorithm

Requires extensive tuning

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the effect of increasing k in kNN?

Has no impact on the algorithm

Reduces the number of neighbors considered

Increases the possibility of errors

Decreases sensitivity to noise

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