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Quizizz-Understanding Unsupervised Learning

Total questions: 10

Worksheet time: 5mins

Name
Class
Date
1.

What is the main goal of unsupervised learning?

a)

To predict outcomes based on labeled data

b)

To uncover patterns and structures in unlabeled data

c)

To fine-tune a model given labeled data

d)

To evaluate model performance using test data

2.

Which of the following is a common clustering algorithm?

a)

Support Vector Machine

b)

K-means clustering

c)

Linear Regression

d)

Random Forest

3.

In anomaly detection, which of the following tasks would be an example?

a)

Categorizing emails into spam or not spam

b)

Detecting fraud in financial transactions

c)

Recommending products based on user behavior

d)

Predicting house prices based on features

4.

Dimensionality reduction is primarily used for which of the following purposes?

a)

To make data easier to manage and visualize

b)

To increase the number of features in a dataset

c)

To classify data into different categories

d)

To evaluate model performance on labeled data

5.

What is the primary application of association mining?

a)

Generating new data samples

b)

Identifying rare events in a dataset

c)

Discovering relationships between data points

d)

Reducing the number of features in a dataset

6.

True or False: Generative modeling can be used to create new synthetic data that resembles the training data.

a)

True

b)

False

7.

Which unsupervised learning application involves segmenting images into meaningful regions?

a)

Topic Modeling

b)

Clustering for Image Segmentation

c)

Density Estimation

d)

Association Mining

8.

True or False: Topic modeling helps in identifying themes in large collections of text data.

a)

True

b)

False

9.

Density estimation is useful for which of the following tasks?

a)

Predicting future sales

b)

Estimating the probability density of data

c)

Classifying images

d)

Clustering similar images together

10.

What type of unsupervised learning is typically used in market basket analysis?

a)

Clustering

b)

Dimensionality Reduction

c)

Association Mining

d)

Anomaly Detection