Search Header Logo

MLII - Nearest Neighbor Methods

Authored by Gabriel Briones

Computers

12th Grade

MLII - Nearest Neighbor Methods
AI

AI Actions

Add similar questions

Adjust reading levels

Convert to real-world scenario

Translate activity

More...

    Content View

    Student View

34 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the main idea behind 'Instance based' classification?

Select the class of the most similar instance

Select the class of the least similar instance

Select the class of the most frequent instance

Select the class of a random instance

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the purpose of distance measures in distance-based machine learning methods?

To find items that are randomly distributed

To find items that are similar based on distance

To find items that are different from each other

To find items that are not mixable

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the function of Term Frequency / Inverse Document Frequency in a vector space?

To calculate the magnitude of vectors

To determine the direction of vectors

To measure the distance between vectors

To identify the importance of a word in a document collection

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How is Cosine similarity used in Information Retrieval?

To classify documents

To rank retrieved documents

To delete irrelevant documents

To create new documents

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the purpose of the k-nearest neighbors algorithm?

To find neighbors with the same age

To find similar items in close proximity

To find the neighbors with the highest salary

To find the most distant neighbors

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the advantage of Weighted Voting in kNN?

It only considers the closest neighbor

It introduces enough variation to prevent ties

It ignores the distance between neighbors

It always counts all neighbors equally

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

In Collaborative Filtering, how are predictions made for a new user?

By ignoring the ratings of other users

By averaging the ratings of the closest neighbors

By assigning the user to the class with the most ratings

By randomly assigning ratings

Access all questions and much more by creating a free account

Create resources

Host any resource

Get auto-graded reports

Google

Continue with Google

Email

Continue with Email

Classlink

Continue with Classlink

Clever

Continue with Clever

or continue with

Microsoft

Microsoft

Apple

Apple

Others

Others

Already have an account?