# Descriptive Analytics

### Purpose

Use this module to explore structure in your data (segments, latent dimensions, associations) and to accelerate EDA.

### Key functions

* `ConductManifoldLearning` — Reduce dimensionality using manifold learning techniques
* `ConductPrincipalComponentAnalysis` — Perform PCA with visualization
* `ConductPropensityScoreMatching` — Create balanced groups for statistical analysis
* `CreateAssociationRules` — Market basket analysis and association rule mining
* `CreateGaussianMixtureClusters` — Probabilistic clustering with Gaussian mixtures
* `CreateHierarchicalClusters` — Hierarchical clustering with dendrograms
* `CreateKMeansClusters` — K-means clustering with automatic visualization
* `GenerateEDAWithLIDA` — AI-powered exploratory data analysis using Microsoft LIDA

### Common use cases

* Customer segmentation
* Dimensionality reduction
* Market basket analysis
* Causal analysis (balanced comparison groups)
* Automated EDA