Classification Algorithms

Introduction

Classification is a supervised learning task where the model learns to predict discrete class labels from labeled training data.

Definition

Classification algorithms are used to categorize input data into predefined classes or categories based on their features.

Types

Binary Classification

Classifying data into two categories

Multiclass Classification

Classifying data into three or more categories

Multilabel Classification

Assigning multiple labels to each instance

Hierarchical Classification

Classification with hierarchical class relationships

Use Cases

• Email spam detection
• Medical diagnosis
• Image recognition
• Sentiment analysis
• Credit risk assessment

Key Points

• Requires labeled training data
• Can handle both linear and non-linear relationships
• Performance depends on feature quality
• Different algorithms suit different problems

References

• Scikit-learn Classification Guide — Comprehensive guide to classification algorithms in scikit-learn