Exploring Regression and Machine Learning

Exploring Regression and Machine Learning

University

15 Qs

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Exploring Regression and Machine Learning

Exploring Regression and Machine Learning

Assessment

Quiz

Information Technology (IT)

University

Practice Problem

Easy

Created by

Sunder Rajini

Used 1+ times

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15 questions

Show all answers

1.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is regression in the context of machine learning?

Regression is a method for predicting continuous outcomes in machine learning.

Regression is a method for optimizing binary outcomes.

Regression is a technique for clustering similar data points.

Regression is used for classifying categorical data.

2.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

Name two common types of regression techniques.

Linear Regression, Logistic Regression

Time Series Regression

Ridge Regression

Polynomial Regression

3.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the purpose of regression evaluation metrics?

To determine the best features for a model

The purpose of regression evaluation metrics is to measure the accuracy and effectiveness of regression models.

To visualize data distributions

To optimize the training speed of models

4.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

List three common regression evaluation metrics.

Mean Absolute Error, Mean Squared Error, R-squared

Precision Score

F1 Score

Accuracy Score

5.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is unsupervised learning?

Unsupervised learning is a machine learning approach that finds patterns in data without labeled outputs.

A process that eliminates noise from data before analysis.

A technique used only for classification tasks.

A method that requires labeled data for training.

6.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

How does clustering differ from classification?

Clustering uses predefined categories, while classification does not.

Clustering is a supervised learning method, while classification is unsupervised.

Clustering requires labeled data, while classification does not.

Clustering groups data without labels, while classification assigns labels based on known categories.

7.

MULTIPLE CHOICE QUESTION

30 sec • 1 pt

What is the main goal of clustering in unsupervised learning?

To group similar data points together.

To predict future outcomes based on historical data.

To reduce the dimensionality of the data.

To classify data points into predefined categories.

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