![]() Alternative Methods for Generating Frequent Itemsets, 3.5 FP-Growth Algorithm, Important Questions Module 2Ģ.1 Introduction, 2.2 Efficient Data Cube computation: An overview, 2.3 Indexing OLAP Data: Bitmap index and join indexĢ.4 Efficient processing of OLAP Queries, 2.5 OLAP server Architecture ROLAP versus MOLAP Versus HOLAPĢ.6 Introduction: What is a data mining, 2.7 Challenges, Data Mining Tasks 2.8 Data: Types of Data,Ģ.9 Data Quality, 2.10 Data Preprocessing, 2.11 Measures of Similarity and Dissimilarity, 2.12 Outcome, 2.13 Important Questions Module 3ģ.1 Introduction, 3.2 Association Analysis: Problem Definition, 3.3 Frequent Itemset Generation,ģ.4 Rule generation. Measures: Their Categorization and computation, 1.9. Dimensions: The role of concept Hierarchiesġ.8. Fact constellations: Schemas for multidimensional Data models, 1.7. Data Cube: A multidimensional data model, Stars, Snowflakesġ.6. ![]() ![]() Extraction, Transformation, and loading, 1.5. Data warehouse models: Enterprise warehouse, Datamart, and virtual warehouseġ.4. Data Warehousing: A multitier Architecture, 1.3.
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