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B.Tech. CSE 8th Sem Subject: Data Mining & Data Warehousing
UNIT - 1 Data ware Housing And Data Mining What is a data warehouse ?, Multidimensional data model, OLAP operation, warehouse schema, data ware housing architecture, warehouse serve, metadata, OLAP, engine, Data
warehousing backend process, other features, What is data mining ?, KDD Vs. data mining, DBMS Vs DM other related areas, DM techniques, other mining problem, issues & challenges in DM, Dm application areas.
UNIT - 2 Association rules what is an association rule ?, methods to discover association rules, a priori algorithm, partition algorithm, pincer – search algorithm, Dynamic Itemset counting algorithm, FP - tree Growth algorithm, Incremental algorithm, Border algorithm, generalized association rules, Association rules with item constraints.
UNIT - 3 Clustering Techniques Introduction, clustering paradigms, partitioning algorithms, k-Medoid Algorithm, CLARA, CLARANS, Hierarchial clustering, DBSCAN, BIRCH, CURE, Categorical clustering algorithms, STIRR, ROCK, CACTUS.
UNIT - 4 Decision Trees What is a Decision tree?, Tree construction principal, Best spilt splitting indices, splitting criteria, Decision tree construction algorithm, CART, ID3, C4.5, CHAID, Decision tree construction with presorting, rainforest, approximate method, CLOUDS, BOAT, pruning technique, integration of pruning & construction.
UNIT - 5 What is neural network ?, Learning in NN, unsupervised learning, data mining using NN, genetic algorithm, Rough sets, Support Vector machines, Web Mining, web content mining, web structure mining, web usage mining, text mining, unstructured text, Episode rule discovery for texts, Hierarchy of categories, text clustering.
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