Core Concepts

• - There are no labels, so pattern quality must be inferred indirectly.
• - Clustering groups similar points by distance or density.
• - Dimensionality reduction reveals compact latent structure.
• - Domain interpretation is required before acting on clusters.

Professional Workflow

1. 1. Standardize and clean high-dimensional features.
2. 2. Select clustering/reduction algorithm by data geometry.
3. 3. Validate with cohesion, separation, and stability checks.
4. 4. Pair results with domain analysis for real decisions.