What is a Classifier?
A classifier is a machine learning model that predicts which category (class) a given input belongs to. It's one of the most fundamental ML concepts: given an input, assign it a label from a predefined set. Spam detection, sentiment analysis, image recognition, and medical diagnosis are all classification tasks.
Why It Matters
Classification is the most widely deployed form of machine learning. Every spam filter, content moderation system, product recommendation engine, fraud detector, and image tagger uses classifiers. Understanding classification is essential for understanding how ML creates value in practice — and it's the foundation upon which more complex AI systems are built.
How It Works
Types of classification:
Binary classification — two possible classes:
- Spam / not spam
- Fraudulent / legitimate
- Positive / negative sentiment
Multi-class classification — multiple classes, one correct:
- Image → cat / dog / bird / fish
- Document → sports / politics / technology / entertainment
Multi-label classification — multiple classes can be correct:
- A movie can be both "action" and "comedy"
- A news article can cover "politics" and "economy"