Home | Amazing | Today | Tags | Publishers | Years | Account | Search 
The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)
The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)

This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of colour graphics. It is a valuable resource...

R and Data Mining: Examples and Case Studies
R and Data Mining: Examples and Case Studies
This book guides R users into data mining and helps data miners who use R in their work. It provides a how-to method using R for data mining applications from academia to industry. It
  • Presents an introduction into using R for data mining applications, covering most popular data mining techniques
  • ...
Data Mining: Concepts, Models, Methods, and Algorithms, Second Edition
Data Mining: Concepts, Models, Methods, and Algorithms, Second Edition
Now updated—the systematic introductory guide to modern analysis of large data sets

As data sets continue to grow in size and complexity, there has been an inevitable move towards indirect, automatic, and intelligent data analysis in which the analyst works via more complex and sophisticated software tools. This book...

Data Mining in Biomedicine (Springer Optimization and Its Applications)
Data Mining in Biomedicine (Springer Optimization and Its Applications)

This volume presents an extensive collection of contributions covering aspects of the exciting and important research field of data mining techniques in biomedicine. Coverage includes new approaches for the analysis of biomedical data; applications of data mining techniques to real-life problems in medical practice; comprehensive...

Social and Political Implications of Data Mining: Knowledge Management in E-Government
Social and Political Implications of Data Mining: Knowledge Management in E-Government
In recent years, data mining has become a powerful tool in assisting society with its various layers and individual elements useful in obtaining intelligent information for making knowledgeable decisions. In the realm of knowledge discovery, data mining is becoming one of the most popular topics in information technology.

Social...

Data Mining and Statistics for Decision Making
Data Mining and Statistics for Decision Making
Data mining is the process of automatically searching large volumes of data for models and patterns using computational techniques from statistics, machine learning and information theory; it is the ideal tool for such an extraction of knowledge. Data mining is usually associated with a business or an organization's need to identify...
Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery (Use R!)
Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery (Use R!)
Data Mining and Anlaytics are the foundation technologies for the new knowledge based world where we build models from data and databases to understand and explore our world. Data mining can improve our business, improve our government, and improve our life and with the right tools, any one can begin to explore this new technology, on the path...
Applied Data Mining
Applied Data Mining

Data mining has witnessed substantial advances in recent decades. New research questions and practical challenges have arisen from emerging areas and applications within the various fields closely related to human daily life, e.g. social media and social networking. This book aims to bridge the gap between traditional data mining and...

Data Mining and Knowledge Discovery for Big Data: Methodologies, Challenge and Opportunities (Studies in Big Data)
Data Mining and Knowledge Discovery for Big Data: Methodologies, Challenge and Opportunities (Studies in Big Data)

The field of data mining has made significant and far-reaching advances over the past three decades. Because of its potential power for solving complex problems, data mining has been successfully applied to diverse areas such as business, engineering, social media, and biological science. Many of these applications search for...

Domain Driven Data Mining
Domain Driven Data Mining

In the present thriving global economy a need has evolved for complex data analysis to enhance an organization’s production systems, decision-making tactics, and performance. In turn, data mining has emerged as one of the most active areas in information technologies. Domain Driven Data Mining offers state-of the-art research and...

Inference Control in Statistical Databases: From Theory to Practice (Lecture Notes in Computer Science)
Inference Control in Statistical Databases: From Theory to Practice (Lecture Notes in Computer Science)
Inference control in statistical databases, also known as statistical disclosure limitation or statistical confidentiality, is about finding tradeoffs to the tension between the increasing societal need for accurate statistical data and the legal and ethical obligation to protect privacy of individuals and enterprises which are the source...
Rough Sets, Fuzzy Sets, Data Mining and Granular Computing: 13th International Conference, RSFDGrC 2011, Moscow, Russia, June 25-27, 2011, Proceedings (Lecture Notes in Computer Science)
Rough Sets, Fuzzy Sets, Data Mining and Granular Computing: 13th International Conference, RSFDGrC 2011, Moscow, Russia, June 25-27, 2011, Proceedings (Lecture Notes in Computer Science)
This book constitutes the refereed proceedings of the 13th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing, R.S.F.D.Gr.C. 2011, held in Moscow, Russia in June 2011. The 49 revised full papers presented together with 5 invited and 2 tutorial papers were carefully reviewed and selected from a total of 83...
Result Page: 55 54 53 52 51 50 49 48 47 46 
©2019 LearnIT (support@pdfchm.net) - Privacy Policy