The book introduces readers to data mining methods and models, including association rules, clustering, K-nearest neighbor, statistical inference, neural networks, linear and logistic regression, and multivariate analysis. Taking a unified approach based on CRISP methodology, the book discusses the latest techniques for uncovering hidden nuggets of information and provides insight into how the data mining algorithms actually work with hands-on experience performing data mining on large data sets. · Dimension Reduction Methods · Regression Modeling · Multiple Regression and Model Building · Logistic Regression · Naïve Bayes and Bayesian Networks · Genetic Algorithms · Case Study: Modeling Response to Direct-Mail Marketing
The book introduces readers to data mining methods and models, including association rules, clustering, K-nearest neighbor, statistical inference, neural networks, linear and logistic regression, and multivariate analysis.
Association rule mining (ARM) is the process of discovering interesting
relationships and associations amongst various items in databases. It primarily
concentrates on transactional databases with the objective of establishing
associations ...
This Book Addresses All The Major And Latest Techniques Of Data Mining And Data Warehousing. It Deals With The Latest Algorithms For Discussing Association Rules, Decision Trees, Clustering, Neural Networks And Genetic Algorithms. The Book Also Discusses The Mining Of Web Data, Temporal And Text Data. It Can Serve As A Textbook For Students Of Compuer Science, Mathematical Science And Management Science, And Also Be An Excellent Handbook For Researchers In The Area Of Data Mining And Warehousing.
This Book Addresses All The Major And Latest Techniques Of Data Mining And Data Warehousing.
Data Mining is the process of analyzing large amount of data in search of previously undiscovered business patterns. Data Warehousing is a relational/multidimensional database that is designed for Query and Analysis rather than Transaction Processing. This book provides a systematic introduction to the principles of Data Mining and Data Warehousing. It covers the entire range of data mining algorithms (prediction, classification, and association), data mining products and applications, stages.
Data Warehousing is a relational/multidimensional database that is designed for Query and Analysis rather than Transaction Processing. This book provides a systematic introduction to the principles of Data Mining and Data Warehousing.
This Book Is Mainly Intended For It Students And Professionals To Learn Or Implement Data Warehousing Technologies. It Experiences The Real-Time Environment And Promotes Planning, Managing, Designing, Implementing, Supporting, Maintaining And Analyzing Data Warehouse In Organizations And It Also Provides Various Mining Techniques As Well As Issues In Practical Use Of Data Mining Tools.The Book Is Designed For The Target Audience Such As Specialists, Trainers And It Users. It Does Not Assume Any Special Knowledge As Background. Understanding Of Computer Use, Databases And Statistics Will Be Helpful.
Introduction 249 1.1 What is Data Mining 251 1.2 Definitions 252 1.3 Data Mining
Process 253 1.4 Data Mining Background 254 1.5 Data Mining Models 256 1.6
Data Mining Methods 257 1.7 Data Mining Problems/Issues 260 1.8 Potential ...
Development of knowledge discovery system from digital library in internet in Indonesia; research report.
Development of knowledge discovery system from digital library in internet in Indonesia; research report.
