Dr. Rambabu Pemula

Unit IV: Unsupervised Learning and Dimensionality Reduction 1.     Types of Unsupervised Learning 2.     Challenges in Unsupervised Learning 3.     Clustering Algorithms a.      K-Means b.     Agglomerative c.      DBSCAN d.     Comparing and Evaluating Clustering Algorithms 4.     Dimensionality Reduction a.      Linear Discriminant Analysis (LDA) b.     Principal Component Analysis (PCA) c.      Factor Analysis (FA) 👉 UNIT-4 (A) Unsupervised Learning Clustering PPT

Unit – IV Unsupervised Learning          1.     Types of Unsupervised Learning 2.     Challenges in Unsupervised Learning 3.     Clustering Algorithms a.      K-Means b.     Agglomerative c.      DBSCAN d.     Comparing and Evaluating Clustering Algorithms            👉  UNIT-4 (A) Unsupervised Learning Clustering PPTs