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SupervisedLearning_Regression

Total questions: 10

Worksheet time: 5mins

Name
Class
Date
1.

Supervised learning algorithms require:

a)

Unlabeled data

b)

Labeled input-output pairs

c)

Only numerical data

d)

Only categorical data

2.

Which of the following is a supervised learning task?

a)

Clustering customer groups

b)

Predicting house prices

c)

Discovering hidden patterns

d)

Topic modeling

3.

In linear regression, the line of best fit is chosen to:

a)

Minimize the total number of data points

b)

Maximize classification accuracy

c)

Minimize the sum of squared errors

d)

Maximize correlation only

4.

The output of linear regression is typically:

a)

A category

b)

A continuous value

c)

A distance metric

d)

A cluster

5.

The train-test split is mainly used to:

a)

Reduce dataset size

b)

Create labels

c)

Evaluate model performance on unseen data

d)

Improve visualization

6.

Which term refers to the difference between predicted and actual values?

a)

Activation

b)

Entropy

c)

Residual(Error)

d)

Kernel

7.

What does the test_size parameter in train_test_split define?

a)

Number of features

b)

Percentage of data used for testing

c)

Model accuracy

d)

Loss function

8.

Which of the following is a commonly used error metric for regression?

a)

Accuracy

b)

Precision

c)

Mean Squared Error (MSE)

d)

Recall

9.

Mean Squared Error (MSE) measures:

a)

Average absolute difference between predictions and actual values

b)

Square root of residuals

c)

Average of squared differences between predictions and actual values

d)

Maximum value in the dataset

10.

If test_size = 0.2, how much data is used for training?

a)

20%

b)

40%

c)

50%

d)

80%