Exploring the Four Key Types
Analyzes unlabeled data to find hidden patterns and groupings.
Uses both labeled and unlabeled data for improved learning efficiency.
Learns through trial and error, optimizing actions based on rewards.
A model that splits data into branches for classification or regression.
Classifies data by finding the best hyperplane in high-dimensional space.
Classifies data based on the majority class of its nearest neighbors.