CS8075 Data Warehousing and Data Mining
CS8075 Data Warehousing and Data Mining MCQ Multi Choice Questions, Lecture Notes, Books, Study Materials, Question Papers, Syllabus Part-A 2 marks with answers CS8075 Data Warehousing and Data Mining MCQ Multi Choice Questions, Subjects Important Part-B 16 marks Questions, PDF Books, Question Bank with answers Key And MCQ Question & Answer, Unit Wise Important Question And Answers, One Mark Question With Answers, Choose The Best Answer.
Download link is provided for Students to download the Anna University CS8075 Data Warehousing and Data Mining MCQ Multi Choice Questions, Lecture Notes, Books, Study Materials, Question Papers, Syllabus Part A 2 marks with answers & Part B 16 marks Question, Question Bank with answers, MCQ Question & Answer, Unit Wise Important Question And Answers, One Mark Question With Answers, Choose The Best Answer. All the materials are listed below for the students to make use of it and score good (maximum) marks with our study materials.
Subject Details
| SEMESTER : | 06 |
| SUBJECT CODE : | CS8075 |
| SUBJECT NAME : | Data Warehousing and Data Mining |
| DEPARTMENT : | Computer Science and Engineering |
| YEAR : | Third Year (III Year) |
| REGULATION : | 2017 |
| CONTENT : | Syllabus, Lecture Notes, Important Part-A 2 Marks Questions and Important Part-B 13 & 15 Mark Questions, Previous Years Question Papers Collections and Question Banks. |
” CS8075 Data Warehousing and Data Mining MCQ Multi Choice Questions”
“ CS8075 Data Warehousing and Data Mining Lecture Notes “
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“ CS8075 Data Warehousing and Data Mining Important Part A & Part B Questions”
“ CS8075 Data Warehousing and Data Mining Syllabus Question Banks”
CS8075 Data Warehousing and Data Mining MCQ Multi Choice Questions, Lecture Notes & Part A & Part B Important Questions with Answers
Syllabus
CS8075 Data Warehousing and Data Mining
UNIT I DATA WAREHOUSING, BUSINESS ANALYSIS AND ON-LINE ANALYTICAL PROCESSING (OLAP)
Basic Concepts – Data Warehousing Components – Building a Data Warehouse – Database Architectures for Parallel Processing – Parallel DBMS Vendors – Multidimensional Data Model – Data Warehouse Schemas for Decision Support, Concept Hierarchies -Characteristics of OLAP Systems – Typical OLAP Operations, OLAP and OLTP.
UNIT II DATA MINING – INTRODUCTION
Introduction to Data Mining Systems – Knowledge Discovery Process – Data Mining Techniques – Issues – applications- Data Objects and attribute types, Statistical description of data, Data Preprocessing – Cleaning, Integration, Reduction, Transformation and discretization, Data Visualization, Data similarity and dissimilarity measures.
UNIT III DATA MINING – FREQUENT PATTERN ANALYSIS
Mining Frequent Patterns, Associations and Correlations – Mining Methods- Pattern Evaluation Method – Pattern Mining in Multilevel, Multi Dimensional Space – Constraint Based Frequent Pattern Mining, Classification using Frequent Patterns
UNIT IV CLASSIFICATION AND CLUSTERING
Decision Tree Induction – Bayesian Classification – Rule Based Classification – Classification by Back Propagation – Support Vector Machines –– Lazy Learners – Model Evaluation and Selection-Techniques to improve Classification Accuracy. Clustering Techniques – Cluster analysis-Partitioning Methods – Hierarchical Methods – Density Based Methods – Grid Based Methods – Evaluation of clustering – Clustering high dimensional data- Clustering with constraints, Outlier analysis-outlier detection methods.
UNIT V WEKA TOOL
Datasets – Introduction, Iris plants database, Breast cancer database, Auto imports database – Introduction to WEKA, The Explorer – Getting started, Exploring the explorer, Learning algorithms, Clustering algorithms, Association–rule learners.
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CS8075 Data Warehousing and Data Mining MCQ Collection
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CS8075 Data Warehousing and Data Mining Unit Wise Notes Collection
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