Data Mining
1066035 modules · 50 topics · 50 with study notes
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Module 1Data Warehousing and Business Analysis9 topics
- Data Warehousing ComponentsNotes
- Building a Data WarehouseNotes
- Data Warehouse ArchitectureNotes
- DBMS Schemas for Decision SupportNotes
- Data Extraction, Cleanup, and Transformation ToolsNotes
- Metadata ReportingNotes
- Query Tools and ApplicationsNotes
- Online Analytical Processing (OLAP)Notes
- OLAP and Multidimensional Data AnalysisNotes
Module 2Data Mining Fundamentals and Association Rule Mining12 topics
- Data Mining FunctionalitiesNotes
- Data PreprocessingNotes
- Data CleaningNotes
- Data Integration and TransformationNotes
- Data ReductionNotes
- Data Discretization and Concept Hierarchy GenerationNotes
- Architecture of a Typical Data Mining SystemNotes
- Classification of Data Mining SystemsNotes
- Efficient and Scalable Frequent Itemset Mining MethodsNotes
- Mining Various Kinds of Association RulesNotes
- Association Mining to Correlation AnalysisNotes
- Constraint-Based Association MiningNotes
Module 3Classification and Prediction14 topics
- Issues Regarding Classification and PredictionNotes
- Classification by Decision Tree InductionNotes
- Bayesian ClassificationNotes
- Rule-Based ClassificationNotes
- Classification by Back PropagationNotes
- Support Vector MachinesNotes
- Associative ClassificationNotes
- Lazy LearnersNotes
- Other Classification MethodsNotes
- PredictionNotes
- Accuracy and Error MeasuresNotes
- Evaluating the Accuracy of a Classifier or PredictorNotes
- Ensemble MethodsNotes
- Model SelectionNotes
Module 4Cluster Analysis10 topics
- Types of Data in Cluster AnalysisNotes
- A Categorization of Major Clustering MethodsNotes
- Partitioning MethodsNotes
- Hierarchical MethodsNotes
- Density-Based MethodsNotes
- Grid-Based MethodsNotes
- Model-Based Clustering MethodsNotes
- Clustering High-Dimensional DataNotes
- Constraint-Based Cluster AnalysisNotes
- Outlier AnalysisNotes
Theory