AI GlossaryClassificationENTRY — Machine Learning
[Machine Learning]
Classification.
Predicting which category or class an input belongs to from a set of predefined categories.
In-depth explanation
01Classification is a supervised learning task where the model learns to assign inputs to discrete categories. Binary classification involves two classes (e.g., spam/not spam), while multi-class classification involves more than two (e.g., digit recognition 0-9). Common algorithms include logistic regression, decision trees, random forests, and neural networks.
Examples
02EX. 01
Spam detection
EX. 02
Image recognition
EX. 03
Sentiment analysis
More in Machine Learning
0301Cross-ValidationA technique to evaluate model performance by training and testing on different subsets of data.02Ensemble LearningCombining multiple models to produce better predictions than any single model.03FeatureAn individual measurable property or characteristic of data used as input to a machine learning model.04Feature EngineeringThe process of using domain knowledge to create new features that improve model performance.05Gradient DescentAn optimization algorithm that iteratively adjusts model parameters to minimize the loss function.06HyperparameterConfiguration settings set before training that control the learning process, not learned from data.
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