CAT - 2 Syllabus

1. Clustering Techniques: Clustering Paradigms, Partitioning Algorithm, k-Medoid Algorithm, CLARA, CLARANS, Hierarchical Clustering, DBSCAN, BIRCH, CURE, Categorical Clustering Algorithms, STIRR, ROCK, CACTUS etc. 6 Hrs.
   
   
2. Decision Trees: What is Decision trees?, Tree Construction, Splitting Criteria, Decision Tree Construction Algorithms, CART, ID3, C4.5, CHAID, Decision tree Construction with Presorting, Rainforest, Approximate methods, CLOUDS, BOAT, Pruning Technique, Integration, an Ideal Algorithm etc. 4 Hrs
   
   
   3. Data Mining Techniques and Algorithms: FP-tree Growth Algorithm, Discussion, Incremental Algorithm, Border Algorithm.