Data Warehousing and Data Mining pdf Notes
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UNIT – I
- Introduction : Fundamentals of data mining, Data Mining Functionalities, Classification of Data Mining systems, Major issues in Data Mining.
- Data Preprocessing : Needs Preprocessing the Data, Data Cleaning, Data Integration and Transformation, Data Reduction, Discretization and Concept Hierarchy Generation.
UNIT – II
- Data Warehouse and OLAP Technology for Data Mining Data Warehouse, Multidimensional Data Model, Data Warehouse Architecture,
- Data Warehouse Implementation, Further Development of Data Cube Technology, From Data Warehousing to Data Mining. Data cube computation and Data Generalization:
- Efficient methods for Data cube computation, Further Development of Data Cube and OLAP Technology, Attribute Oriented Induction.
UNIT – III
- Mining Frequent Patterns, Associations And Correlations, Basic Concepts. Efficient And Scalable Frequent Itemset Mining Methods Mining Various Kinds Of Association Rules,
- From Associative Mining To Correlation Analysis, Constraint Based Association Mining.
UNIT – IV
- Classification and Prediction : Issues Regarding Classification and Prediction, Classification by Decision Tree Induction,
- Bayesian Classification, Classification by Backpropagation, Support Vector Machines , Associative Classification, Lazy Learners ,
- Other Classification Methods, Prediction, Accuracy and Error Measures, Evaluating the accuracy of Classifier or a predictor, Ensemble methods.
UNIT – V
- Cluster Analysis Introduction : Types of Data in Cluster Analysis, A Categorization of Major Clustering Methods,
- Partitioning Methods, Density-Based Methods, Grid-Based Methods, Model-Based Clustering Methods, Outlier Analysis.
UNIT – VI
- Mining Streams, Time Series and Sequence Data: Mining Data Streams Mining Time Series Data, Mining Sequence Patterns in Transactional Databases,
- Mining Sequence Patterns in biological Data, Graph Mining, Social Network Analysis and Multi Relational Data Mining
UNIT – VII
- Mining Object, Spatial , Multimedia, Text and Web Data: Multidimensional Analysis and Descriptive mining of Complex Data objects, Spatial Data Mining, Multimedia Data Mining , Text Mining, Mining of the World WideWeb.
UNIT – VIII
- Applications and Trends In Data Mining : Data mining applications, Data Mining Products and Research Prototypes, Additional Themes on Data Mining and Social Impacts Of Data Mining.
TEXT BOOKS :
- Data Mining – Concepts and Techniques – JIAWEI HAN & MICHELINE KAMBER Harcourt India.2nd ed 2006
- introduction to data mining- pang-ning tan, micheal steinbach and vipin kumar, pearson education.
- Data Mining Introductory and advanced topics –MARGARET H DUNHAM, PEARSON EDUCATION
- Data Mining Techniques – ARUN K PUJARI, University Press.
- Data Warehousing in the Real World – SAM ANAHORY & DENNIS MURRAY. Pearson Edn Asia.
- Data Warehousing Fundamentals – PAULRAJ PONNAIAH WILEY STUDENT EDITION.
- The Data Warehouse Life cycle Tool kit – RALPH KIMBALL WILEY STUDENT EDITION.