Machine Learning and Data Mining

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  • Author : Igor Kononenko
  • Publisher : Elsevier
  • Pages : 480 pages
  • ISBN : 0857099442
  • Rating : /5 from reviews
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Download or Read online Machine Learning and Data Mining full in PDF, ePub and kindle. this book written by Igor Kononenko and published by Elsevier which was released on 30 April 2007 with total page 480 pages. We cannot guarantee that Machine Learning and Data Mining book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. Data mining is often referred to by real-time users and software solutions providers as knowledge discovery in databases (KDD). Good data mining practice for business intelligence (the art of turning raw software into meaningful information) is demonstrated by the many new techniques and developments in the conversion of fresh scientific discovery into widely accessible software solutions. This book has been written as an introduction to the main issues associated with the basics of machine learning and the algorithms used in data mining. Suitable for advanced undergraduates and their tutors at postgraduate level in a wide area of computer science and technology topics as well as researchers looking to adapt various algorithms for particular data mining tasks. A valuable addition to the libraries and bookshelves of the many companies who are using the principles of data mining (or KDD) to effectively deliver solid business and industry solutions. Provides an introduction to the main issues associated with the basics of machine learning and the algorithms used in data mining A valuable addition to the libraries and bookshelves of companies using the principles of data mining (or KDD) to effectively deliver solid business and industry solutions

Machine Learning and Data Mining

Machine Learning and Data Mining
  • Author : Igor Kononenko,Matjaz Kukar
  • Publisher : Elsevier
  • Release : 30 April 2007
GET THIS BOOK Machine Learning and Data Mining

Data mining is often referred to by real-time users and software solutions providers as knowledge discovery in databases (KDD). Good data mining practice for business intelligence (the art of turning raw software into meaningful information) is demonstrated by the many new techniques and developments in the conversion of fresh scientific discovery into widely accessible software solutions. This book has been written as an introduction to the main issues associated with the basics of machine learning and the algorithms used in

Artificial Intelligence and Data Mining in Healthcare

Artificial Intelligence and Data Mining in Healthcare
  • Author : Malek Masmoudi,Bassem Jarboui,Patrick Siarry
  • Publisher : Springer Nature
  • Release : 02 February 2023
GET THIS BOOK Artificial Intelligence and Data Mining in Healthcare

This book presents recent work on healthcare management and engineering using artificial intelligence and data mining techniques. Specific topics covered in the contributed chapters include predictive mining, decision support, capacity management, patient flow optimization, image compression, data clustering, and feature selection. The content will be valuable for researchers and postgraduate students in computer science, information technology, industrial engineering, and applied mathematics.

Machine Learning and Data Mining in Pattern Recognition

Machine Learning and Data Mining in Pattern Recognition
  • Author : Petra Perner
  • Publisher : Springer Science & Business Media
  • Release : 21 July 2009
GET THIS BOOK Machine Learning and Data Mining in Pattern Recognition

There is no royal road to science, and only those who do not dread the fatiguing climb of its steep paths have a chance of gaining its luminous summits. Karl Marx A Universial Genius of the 19th Century Many scientists from all over the world during the past two years since the MLDM 2007 have come along on the stony way to the sunny summit of science and have worked hard on new ideas and applications in the area of data

Artificial Intelligence and Data Mining Approaches in Security Frameworks

Artificial Intelligence and Data Mining Approaches in Security Frameworks
  • Author : Neeraj Bhargava,Ritu Bhargava,Pramod Singh Rathore,Rashmi Agrawal
  • Publisher : John Wiley & Sons
  • Release : 24 August 2021
GET THIS BOOK Artificial Intelligence and Data Mining Approaches in Security Frameworks

ARTIFICIAL INTELLIGENCE AND DATA MINING IN SECURITY FRAMEWORKS Written and edited by a team of experts in the field, this outstanding new volume offers solutions to the problems of security, outlining the concepts behind allowing computers to learn from experience and understand the world in terms of a hierarchy of concepts, with each concept defined through its relation to simpler concepts. Artificial intelligence (AI) and data mining is the fastest growing field in computer science. AI and data mining

Artificial Intelligence in Data Mining

Artificial Intelligence in Data Mining
  • Author : D. Binu,B.R. Rajakumar
  • Publisher : Academic Press
  • Release : 17 February 2021
GET THIS BOOK Artificial Intelligence in Data Mining

Artificial Intelligence in Data Mining: Theories and Applications offers a comprehensive introduction to data mining theories, relevant AI techniques, and their many real-world applications. This book is written by experienced engineers for engineers, biomedical engineers, and researchers in neural networks, as well as computer scientists with an interest in the area. Provides coverage of the fundamentals of Artificial Intelligence as applied to data mining, including computational intelligence and unsupervised learning methods for data clustering Presents coverage of key topics such

Artificial Intelligence and Data Mining for Mergers and Acquisitions

Artificial Intelligence and Data Mining for Mergers and Acquisitions
  • Author : Debasis Chanda
  • Publisher : CRC Press
  • Release : 18 March 2021
GET THIS BOOK Artificial Intelligence and Data Mining for Mergers and Acquisitions

The goal of this book is to present a modeling framework for the Virtual Organization that is focused on process composition. This framework uses Predicate Calculus Knowledge Bases. Petri Net-based modeling is also discussed. In this context, a Data Mining model is proposed, using a fuzzy mathematical approach, aiming to discover knowledge. A Knowledge-Based framework has been proposed in order to present an all-inclusive knowledge store for static and dynamic properties. Toward this direction, a Knowledge Base is created, and

Artificial Intelligence and Data Mining Approaches in Security Frameworks

Artificial Intelligence and Data Mining Approaches in Security Frameworks
  • Author : Neeraj Bhargava,Ritu Bhargava,Pramod Singh Rathore,Rashmi Agrawal
  • Publisher : John Wiley & Sons
  • Release : 11 August 2021
GET THIS BOOK Artificial Intelligence and Data Mining Approaches in Security Frameworks

Artificial intelligence (AI) and data mining is the fastest growing field in computer science. AI and data mining algorithms and techniques are found to be useful in different areas like pattern recognition, automatic threat detection, automatic problem solving, visual recognition, fraud detection, detecting developmental delay in children, and many other applications. However, applying AI and data mining techniques or algorithms successfully in these areas needs a concerted effort, fostering integrative research between experts ranging from diverse disciplines from data science

Artificial Intelligence in Data Mining

Artificial Intelligence in Data Mining
  • Author : D. Binu,B.R. Rajakumar
  • Publisher : Academic Press
  • Release : 08 March 2021
GET THIS BOOK Artificial Intelligence in Data Mining

Artificial Intelligence in Data Mining: Theories and Applications offers a comprehensive introduction to data mining theories, relevant AI techniques, and their many real-world applications. This book is written by experienced engineers for engineers, biomedical engineers, and researchers in neural networks, as well as computer scientists with an interest in the area. Provides coverage of the fundamentals of Artificial Intelligence as applied to data mining, including computational intelligence and unsupervised learning methods for data clustering Presents coverage of key topics such

Machine Learning and Data Mining in Pattern Recognition

Machine Learning and Data Mining in Pattern Recognition
  • Author : Petra Perner,Azriel Rosenfeld
  • Publisher : Springer Science & Business Media
  • Release : 25 June 2003
GET THIS BOOK Machine Learning and Data Mining in Pattern Recognition

TheInternationalConferenceonMachineLearningandDataMining(MLDM)is the third meeting in a series of biennial events, which started in 1999, organized by the Institute of Computer Vision and Applied Computer Sciences (IBaI) in Leipzig. MLDM began as a workshop and is now a conference, and has brought the topic of machine learning and data mining to the attention of the research community. Seventy-?ve papers were submitted to the conference this year. The program committeeworkedhardtoselectthemostprogressiveresearchinafairandc- petent review process which led to the acceptance of 33 papers

Data Mining and Machine Learning Applications

Data Mining and Machine Learning Applications
  • Author : Rohit Raja,Kapil Kumar Nagwanshi,Sandeep Kumar,K. Ramya Laxmi
  • Publisher : John Wiley & Sons
  • Release : 26 January 2022
GET THIS BOOK Data Mining and Machine Learning Applications

DATA MINING AND MACHINE LEARNING APPLICATIONS The book elaborates in detail on the current needs of data mining and machine learning and promotes mutual understanding among research in different disciplines, thus facilitating research development and collaboration. Data, the latest currency of today’s world, is the new gold. In this new form of gold, the most beautiful jewels are data analytics and machine learning. Data mining and machine learning are considered interdisciplinary fields. Data mining is a subset of data

Data Mining for Business Applications

Data Mining for Business Applications
  • Author : C. Soares,Rayid Ghani
  • Publisher : IOS Press
  • Release : 02 February 2023
GET THIS BOOK Data Mining for Business Applications

Data mining is already incorporated into the business processes in sectors such as health, retail, automotive, finance, telecom and insurance as well as in government. This book contains extended versions of a selection of papers presented at a series of workshops held between 2005 and 2008 on the subject of data mining for business applications.

Metalearning

Metalearning
  • Author : Pavel Brazdil
  • Publisher : Springer Nature
  • Release : 02 February 2023
GET THIS BOOK Metalearning

This open access book as one of the fastest-growing areas of research in machine learning, metalearning studies principled methods to obtain efficient models and solutions by adapting machine learning and data mining processes. This adaptation usually exploits information from past experience on other tasks and the adaptive processes can involve machine learning approaches. As a related area to metalearning and a hot topic currently, automated machine learning (AutoML) is concerned with automating the machine learning processes. Metalearning and AutoML can

Predictive Data Mining

Predictive Data Mining
  • Author : Sholom M. Weiss,Nitin Indurkhya
  • Publisher : Morgan Kaufmann
  • Release : 02 February 1998
GET THIS BOOK Predictive Data Mining

This book is the first technical guide to provide a complete, generalized road map for developing data-mining applications, together with advice on performing these large-scale, open-ended analyses for real-world data warehouses.

Nature Inspired Computation in Data Mining and Machine Learning

Nature Inspired Computation in Data Mining and Machine Learning
  • Author : Xin-She Yang,Xing-Shi He
  • Publisher : Springer Nature
  • Release : 03 September 2019
GET THIS BOOK Nature Inspired Computation in Data Mining and Machine Learning

This book reviews the latest developments in nature-inspired computation, with a focus on the cross-disciplinary applications in data mining and machine learning. Data mining, machine learning and nature-inspired computation are current hot research topics due to their importance in both theory and practical applications. Adopting an application-focused approach, each chapter introduces a specific topic, with detailed descriptions of relevant algorithms, extensive literature reviews and implementation details. Covering topics such as nature-inspired algorithms, swarm intelligence, classification, clustering, feature selection, cybersecurity, learning

Data Mining and Machine Learning in Cybersecurity

Data Mining and Machine Learning in Cybersecurity
  • Author : Sumeet Dua,Xian Du
  • Publisher : CRC Press
  • Release : 25 April 2011
GET THIS BOOK Data Mining and Machine Learning in Cybersecurity

With the rapid advancement of information discovery techniques, machine learning and data mining continue to play a significant role in cybersecurity. Although several conferences, workshops, and journals focus on the fragmented research topics in this area, there has been no single interdisciplinary resource on past and current works and possible paths for future research in this area. This book fills this need. From basic concepts in machine learning and data mining to advanced problems in the machine learning domain, Data