# Lecture Notes for Cluster Analysis

[Lecture 1: Measures of Similarity](lec1)

[Lecture 2.1: Distance Measures Reasoning](lec2-1)

[Lecture 2.2: Principle Component Analysis Pt. 1](lec2-2)

Lecture 3: Discussion of Dataset

[Lecture 4: Principal Component Analysis Pt. 2](lec4)

[Lecture 4.2: Revisiting Measures](lec4-2)

[Lecture 4.3: Cluster Tendency](lec4-3)

[Lecture 5: Introduction to Connectivity Based Models](lec5)

[Lecture 6: Agglomerative Methods](lec6)

[Lecture 7: Divisive Methods Part 1: Monothetic](lec7)

[Lecture 8: Divisive Methods Part 2: Polythetic](lec8)

[Lecture 9.1: CURE and TSNE](lec9-1)

[Lecture 9.2: Cluster Validation Part I](lec9-2)

[Lecture 10.1: Silhouette Coefficient](lec10-1)

[Lecture 10.2: Centroid-Based Clustering](lec10-2)

[Lecture 10.3: Voronoi Diagrams](lec10-3)

[Lecture 11.1: K-means++](lec11-1)

[Lecture 11.2: K-medoids](lec11-2)

[Lecture 11.3: K-medians](lec11-3)

[Lecture 12: Introduction to Density Based Clustering](lec12)