Unsupervised learning

As explained in Advanced Algorithms and Data Structures

Unsupervised learning is machine learning that analyzes unlabeled data to discover structure or patterns without predefined categories.

How Advanced Algorithms and Data Structures covers it

How deep it goes

Explains the objective through clustering, then compares algorithms, evaluation metrics, and hyper-parameter selection.

Examples

Uses customer segmentation, signal-noise detection, unusual-point discovery, and grouping people by demographic and financial attributes.

What you can do after

Apply it via clustering to group unlabeled points, inspect discovered categories, detect noise, and prepare data for later algorithms.

How it connects

Connects unsupervised learning with supervised learning, reinforcement learning, clustering, k-means, DBSCAN, OPTICS, and nearest neighbor search.

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Related concepts

• supervised learningcontrasts with · Supervised learning is a machine-learning approach that learns to map inputs to target outputs from examples paired with known labels or values.
• K-means clusteringincludes · K-means clustering partitions data into a specified number of groups by assigning observations to representative centers and iteratively updating those centers to reduce within-group distances.
• density estimatorincludes · A density estimator is a statistical method or model that estimates the probability density underlying observed data.
• hierarchical clusteringincludes · Hierarchical clustering is a clustering method that organizes observations into nested groups by successively merging or splitting clusters.
• machine learningkind of · Machine learning is a field of computational methods in which systems learn patterns or relationships from data to make predictions, decisions, or other outputs.
• clusteringincludes · Clustering is the technique of grouping data items according to similarity or shared characteristics.

This explainer was generated by Manning's knowledge graph from the text of Advanced Algorithms and Data Structures. The section links point to the parts of the book it draws on.