BCA 604 (C) : Data Mining
BCA 604 (C) : Data Mining

BCA 604 (C) : Data Mining

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Publisher: Prime Publishing House
ISBN: 9789395605755
Year: 2024
Pages: 118

This textbook on Data Mining provides a comprehensive introduction to the techniques and concepts used to extract meaningful information from large datasets. It covers the fundamentals of data warehousing, multidimensional data models, OLAP operations, and the overall architecture required for effective data analysis.

The book explores key data mining techniques such as classification, prediction, clustering, and association rule mining, along with important models like decision trees, Bayesian classification, and support vector machines. It also addresses practical aspects including pattern analysis, data mining processes, and real-world applications across various domains.

Written in a clear and easy-to-understand style, the content is supported with examples and practical insights to help learners develop analytical thinking and problem-solving skills. This book serves as a valuable resource for students and beginners aiming to build a strong foundation in data mining and explore opportunities in the rapidly growing field of data analytics.

1. Introduction to Data Warehousing
1.1 Introduction
1.2 What is Data Warehouse?
1.3 Multidimensional Data Model
1.4 OLAP Operations
1.5 Warehouse Schema
1.6 Data Warehouse Architecture
1.7 Warehouse Server
1.8 Metadata
1.9 OLAP Engine
1.10 Data Warehouse Backend Process

2. Introduction to Data Mining
2.1 What is Data Mining?
2.2 History of Data Mining
2.3 Types of Data
2.4 Data Mining Techniques
2.5 Data Mining Implementation Process
2.6 Data Mining vs Machine Learning

3. Basics of Data Mining & Models
3.1 Introduction to Data Mining Functionalities
3.2 Issues in Data Mining
3.3 Data Mining Architecture
3.4 Data Mining Models
3.5 Types of data mining models
3.6 Interestingness of Patterns
3.7 Classification of Data Mining Systems
3.8 Data Mining Task.

4. Association Rule Mining
4.1 Mining Frequent Patterns
4.2 Associations and Correlations
4.3 Mining Methods
4.4 Mining Various Kinds of Association
4.5 Rules
4.6 Correlation Analysis
4.7 Constraint Based Association Mining

5. Classification of Data Mining
5.1 Classification and Prediction - Basic concepts
5.2 Decision Tree Induction, Bayesian Classification
5.3 Rule Based classification
5.4 Classification by Back propagation
5.5 Support Vector Machines

6. Clustering & Applications
6.1 Cluster analysis
6.2 Categorization of Major Clustering methods
6.3 K-means partitioning methods
6.4 Hierarchical Methods- Data Mining Applications

BCA-604 (C) | Semester VI BACHELOR OF COMPUTER APPLICATIONS (BCA) As per U.G.C. guidelines and also on the basis of the revised syllabus of Kaviyatri Bahinabai Chaudhary North Maharashtra University with effect from Academic Year 2024-25. Also useful for all Universities.

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Rs. 140.00
Rs. 155.00
Rs. 140.00
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Example product title
Rs. 140.00
Rs. 155.00
Rs. 140.00
(-10%)
Example product title
Rs. 140.00
Rs. 155.00
Rs. 140.00
(-10%)
Example product title
Rs. 140.00
Rs. 155.00
Rs. 140.00
(-10%)
Example product title
Rs. 140.00
Rs. 155.00
Rs. 140.00
(-10%)
Example product title
Rs. 140.00
Rs. 155.00
Rs. 140.00
(-10%)
Example product title
Rs. 140.00
Rs. 155.00
Rs. 140.00
(-10%)
Example product title
Rs. 140.00
Rs. 155.00
Rs. 140.00
(-10%)
Example product title
Rs. 140.00
Rs. 155.00
Rs. 140.00
(-10%)
Example product title
Rs. 140.00
Rs. 155.00
Rs. 140.00
(-10%)

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