What Is Classification in Machine Learning?
Classification is a type of machine learning where the model learns to assign input data to one of several categories. For example: is this email spam or not spam? Is this fruit an apple, banana, or mango?
About This Resource
Classification is how AI sorts things into categories. Learn how decision trees and classifiers work through step-by-step examples.
Machine learning classification resource suitable for Class 7–9 students.
What Students Will Learn
- Define classification and give three real-world examples
- Explain how a decision tree makes classification decisions
- Build a simple decision tree for a classification problem
- Understand binary and multi-class classification
Resources Available
Questions & Answers
What is classification in machine learning?
Classification is a type of machine learning where the model learns to assign input data to one of several categories. For example: is this email spam or not spam? Is this fruit an apple, banana, or mango?
What is a decision tree?
A decision tree is a classification algorithm that makes decisions by asking a series of yes/no questions. Each question splits the data further until a final category is assigned — like following a flowchart.
What are examples of classification AI?
Spam filters (spam/not spam), medical diagnosis (disease/no disease), face recognition (which person?), image labelling (cat/dog/bird), and sentiment analysis (positive/negative) are all classification problems.
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