Classification is a type of supervised learning in artificial intelligence where the goal is to assign input data into predefined categories or classes. The model learns from labeled training data to predict the category of new, unseen data.
Characteristics:
– Works with discrete labels or categories
– Requires a labeled dataset for training
– Outputs a class label for each input
– Commonly used for decision-making tasks
Examples:
– Email spam detection (spam or not spam)
– Image recognition (identifying objects like cats, dogs, cars)
– Medical diagnosis (classifying diseases based on symptoms)
– Sentiment analysis (positive, negative, or neutral sentiment in text)
