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UNIT‐1: Introduction of Data Mining , Data warehouse and OLAP
- Motivation: Why data mining?
- What is data mining?
- Data Mining: On what kind of data?
- Data mining functionality?
- Classification of data mining systems
- Major issues in data mining
- What is a data warehouse?
- A multi‐dimensional data model
- Data warehouse architecture
- Data warehouse implementation
- Data warehouse implementation
- From data warehousing to data mining
UNIT‐2: Data Pre-processing
- Why preprocess the data?
- Data cleaning
- Data integration and transformation
- Data reduction
- Discretization and concept hierarch generation
UNIT‐3: Data Mining Primitives, Languages, and System Architectures
- Data mining primitives: What defines a data mining task?
- A data mining query language
- Design graphical user interfaces based on a data mining query language
- Architecture of data mining systems
UNIT‐4: Characterization and Comparison
- What is concept description?
- Data generalization and summarization‐based characterization
- Analytical characterization:Analysis of attribute relevance
- Mining class comparisons: Discriminating between different classes
- Mining descriptive statistical measures in large databases
UNIT‐5: Mining Association Rules in Large Databases
- Association rule mining
- Mining single‐dimensional Boolean association rules from transactional databases
- Mining multilevel association rules from transactional databases
- Mining multidimensional association rules from transactional databases and data warehouse
- From association mining to correlation analysis
- Constraint‐based association mining
UNIT‐6: Classification and Prediction
- What is classification? What is prediction?
- Issues regarding classification and prediction
- Classification by decision tree induction
- Bayesian Classification
- Classification by backpropagation
- Classification based on concepts from association rule mining
- Other Classification Methods
- Classification accuracy
UNIT‐7: Cluster Analysis
- What is Cluster Analysis?
- Types of Data in Cluster Analysis
- A Categorization of Major Clustering Methods
- Partitioning Methods
- Hierarchical Methods
- Density‐Based Methods
- Grid‐Based Methods
- Model‐Based Clustering Methods
- Outlier Analysis
UNIT‐8: Mining Complex Types of Data
- Multidimensional analysis and descriptive mining of complex data objects
- Mining spatial databases
- Mining multimedia databases
- Mining time‐series and sequence data
- Mining text databases
- Mining the World‐Wide Web
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