Machine Learning Techniques In Data Mining Applications

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Data Mining and Machine Learning Applications

Author : Rohit Raja
Publisher : John Wiley & Sons
ISBN 13 : 1119792509
Total Pages : 500 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Data Mining and Machine Learning Applications by : Rohit Raja

Download or read book Data Mining and Machine Learning Applications written by Rohit Raja and published by John Wiley & Sons. This book was released on 2022-01-26 with total page 500 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 analytics and machine learning involves the use of algorithms that automatically improve through experience based on data. Massive datasets can be classified and clustered to obtain accurate results. The most common technologies used include classification and clustering methods. Accuracy and error rates are calculated for regression and classification and clustering to find actual results through algorithms like support vector machines and neural networks with forward and backward propagation. Applications include fraud detection, image processing, medical diagnosis, weather prediction, e-commerce and so forth. The book features: A review of the state-of-the-art in data mining and machine learning, A review and description of the learning methods in human-computer interaction, Implementation strategies and future research directions used to meet the design and application requirements of several modern and real-time applications for a long time, The scope and implementation of a majority of data mining and machine learning strategies. A discussion of real-time problems. Audience Industry and academic researchers, scientists, and engineers in information technology, data science and machine and deep learning, as well as artificial intelligence more broadly.

Machine Learning and Data Mining

Author : Ryszad S. Michalski
Publisher : Wiley
ISBN 13 : 9780471971993
Total Pages : 472 pages
Book Rating : 4.9/5 (719 download)

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Book Synopsis Machine Learning and Data Mining by : Ryszad S. Michalski

Download or read book Machine Learning and Data Mining written by Ryszad S. Michalski and published by Wiley. This book was released on 1998-04-22 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master the new computational tools to get the most out of your information system. This practical guide, the first to clearly outline the situation for the benefit of engineers and scientists, provides a straightforward introduction to basic machine learning and data mining methods, covering the analysis of numerical, text, and sound data.

Data Mining

Author : Ian H. Witten
Publisher : Elsevier
ISBN 13 : 0080890369
Total Pages : 665 pages
Book Rating : 4.0/5 (88 download)

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Book Synopsis Data Mining by : Ian H. Witten

Download or read book Data Mining written by Ian H. Witten and published by Elsevier. This book was released on 2011-02-03 with total page 665 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including new material on Data Transformations, Ensemble Learning, Massive Data Sets, Multi-instance Learning, plus a new version of the popular Weka machine learning software developed by the authors. Witten, Frank, and Hall include both tried-and-true techniques of today as well as methods at the leading edge of contemporary research. The book is targeted at information systems practitioners, programmers, consultants, developers, information technology managers, specification writers, data analysts, data modelers, database R&D professionals, data warehouse engineers, data mining professionals. The book will also be useful for professors and students of upper-level undergraduate and graduate-level data mining and machine learning courses who want to incorporate data mining as part of their data management knowledge base and expertise. Provides a thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques to your data mining projects Offers concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods Includes downloadable Weka software toolkit, a collection of machine learning algorithms for data mining tasks—in an updated, interactive interface. Algorithms in toolkit cover: data pre-processing, classification, regression, clustering, association rules, visualization

Data Mining and Machine Learning

Author : Mohammed J. Zaki
Publisher : Cambridge University Press
ISBN 13 : 1108473989
Total Pages : 779 pages
Book Rating : 4.1/5 (84 download)

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Book Synopsis Data Mining and Machine Learning by : Mohammed J. Zaki

Download or read book Data Mining and Machine Learning written by Mohammed J. Zaki and published by Cambridge University Press. This book was released on 2020-01-30 with total page 779 pages. Available in PDF, EPUB and Kindle. Book excerpt: New to the second edition of this advanced text are several chapters on regression, including neural networks and deep learning.

MACHINE LEARNING TECHNIQUES IN DATA MINING APPLICATIONS

Author : DR. SUBHENDU KUMAR PANI
Publisher : Lulu.com
ISBN 13 : 1365016242
Total Pages : 227 pages
Book Rating : 4.3/5 (65 download)

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Book Synopsis MACHINE LEARNING TECHNIQUES IN DATA MINING APPLICATIONS by : DR. SUBHENDU KUMAR PANI

Download or read book MACHINE LEARNING TECHNIQUES IN DATA MINING APPLICATIONS written by DR. SUBHENDU KUMAR PANI and published by Lulu.com. This book was released on with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Machine Learning and Data Mining for Computer Security

Author : Marcus A. Maloof
Publisher : Springer Science & Business Media
ISBN 13 : 1846282535
Total Pages : 218 pages
Book Rating : 4.8/5 (462 download)

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Book Synopsis Machine Learning and Data Mining for Computer Security by : Marcus A. Maloof

Download or read book Machine Learning and Data Mining for Computer Security written by Marcus A. Maloof and published by Springer Science & Business Media. This book was released on 2006-02-27 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Machine Learning and Data Mining for Computer Security" provides an overview of the current state of research in machine learning and data mining as it applies to problems in computer security. This book has a strong focus on information processing and combines and extends results from computer security. The first part of the book surveys the data sources, the learning and mining methods, evaluation methodologies, and past work relevant for computer security. The second part of the book consists of articles written by the top researchers working in this area. These articles deals with topics of host-based intrusion detection through the analysis of audit trails, of command sequences and of system calls as well as network intrusion detection through the analysis of TCP packets and the detection of malicious executables. This book fills the great need for a book that collects and frames work on developing and applying methods from machine learning and data mining to problems in computer security.

Data Mining

Author : Derya Birant
Publisher : BoD – Books on Demand
ISBN 13 : 183968318X
Total Pages : 214 pages
Book Rating : 4.8/5 (396 download)

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Book Synopsis Data Mining by : Derya Birant

Download or read book Data Mining written by Derya Birant and published by BoD – Books on Demand. This book was released on 2021-01-20 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining is a branch of computer science that is used to automatically extract meaningful, useful knowledge and previously unknown, hidden, interesting patterns from a large amount of data to support the decision-making process. This book presents recent theoretical and practical advances in the field of data mining. It discusses a number of data mining methods, including classification, clustering, and association rule mining. This book brings together many different successful data mining studies in various areas such as health, banking, education, software engineering, animal science, and the environment.

Artificial Intelligence in Data Mining

Author : D. Binu
Publisher : Academic Press
ISBN 13 : 0128206160
Total Pages : 270 pages
Book Rating : 4.1/5 (282 download)

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Book Synopsis Artificial Intelligence in Data Mining by : D. Binu

Download or read book Artificial Intelligence in Data Mining written by D. Binu and published by Academic Press. This book was released on 2021-02-17 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 as heuristic methods for data clustering, deep learning methods for data classification, and neural networks Includes case studies and real-world applications of AI techniques in data mining, for improved outcomes in clinical diagnosis, satellite data extraction, agriculture, security and defense

Data Mining for Business Analytics

Author : Galit Shmueli
Publisher : John Wiley & Sons
ISBN 13 : 1119549841
Total Pages : 610 pages
Book Rating : 4.1/5 (195 download)

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Book Synopsis Data Mining for Business Analytics by : Galit Shmueli

Download or read book Data Mining for Business Analytics written by Galit Shmueli and published by John Wiley & Sons. This book was released on 2019-11-05 with total page 610 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python presents an applied approach to data mining concepts and methods, using Python software for illustration Readers will learn how to implement a variety of popular data mining algorithms in Python (a free and open-source software) to tackle business problems and opportunities. This is the sixth version of this successful text, and the first using Python. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining and network analysis. It also includes: A new co-author, Peter Gedeck, who brings both experience teaching business analytics courses using Python, and expertise in the application of machine learning methods to the drug-discovery process A new section on ethical issues in data mining Updates and new material based on feedback from instructors teaching MBA, undergraduate, diploma and executive courses, and from their students More than a dozen case studies demonstrating applications for the data mining techniques described End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, PowerPoint slides, and case solutions Data Mining for Business Analytics: Concepts, Techniques, and Applications in Python is an ideal textbook for graduate and upper-undergraduate level courses in data mining, predictive analytics, and business analytics. This new edition is also an excellent reference for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology. “This book has by far the most comprehensive review of business analytics methods that I have ever seen, covering everything from classical approaches such as linear and logistic regression, through to modern methods like neural networks, bagging and boosting, and even much more business specific procedures such as social network analysis and text mining. If not the bible, it is at the least a definitive manual on the subject.” —Gareth M. James, University of Southern California and co-author (with Witten, Hastie and Tibshirani) of the best-selling book An Introduction to Statistical Learning, with Applications in R

Metalearning

Author : Pavel Brazdil
Publisher : Springer Science & Business Media
ISBN 13 : 3540732624
Total Pages : 182 pages
Book Rating : 4.5/5 (47 download)

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Book Synopsis Metalearning by : Pavel Brazdil

Download or read book Metalearning written by Pavel Brazdil and published by Springer Science & Business Media. This book was released on 2008-11-26 with total page 182 pages. Available in PDF, EPUB and Kindle. Book excerpt: Metalearning is the study of principled methods that exploit metaknowledge to obtain efficient models and solutions by adapting machine learning and data mining processes. While the variety of machine learning and data mining techniques now available can, in principle, provide good model solutions, a methodology is still needed to guide the search for the most appropriate model in an efficient way. Metalearning provides one such methodology that allows systems to become more effective through experience. This book discusses several approaches to obtaining knowledge concerning the performance of machine learning and data mining algorithms. It shows how this knowledge can be reused to select, combine, compose and adapt both algorithms and models to yield faster, more effective solutions to data mining problems. It can thus help developers improve their algorithms and also develop learning systems that can improve themselves. The book will be of interest to researchers and graduate students in the areas of machine learning, data mining and artificial intelligence.

Data Mining and Analysis

Author : Mohammed J. Zaki
Publisher : Cambridge University Press
ISBN 13 : 0521766338
Total Pages : 607 pages
Book Rating : 4.5/5 (217 download)

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Book Synopsis Data Mining and Analysis by : Mohammed J. Zaki

Download or read book Data Mining and Analysis written by Mohammed J. Zaki and published by Cambridge University Press. This book was released on 2014-05-12 with total page 607 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive overview of data mining from an algorithmic perspective, integrating related concepts from machine learning and statistics.

Machine Learning and Data Mining for Emerging Trend in Cyber Dynamics

Author : Haruna Chiroma
Publisher : Springer Nature
ISBN 13 : 3030662888
Total Pages : 316 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Machine Learning and Data Mining for Emerging Trend in Cyber Dynamics by : Haruna Chiroma

Download or read book Machine Learning and Data Mining for Emerging Trend in Cyber Dynamics written by Haruna Chiroma and published by Springer Nature. This book was released on 2021-04-01 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses theories and empirical procedures for the application of machine learning and data mining to solve problems in cyber dynamics. It explains the fundamentals of cyber dynamics, and presents how these resilient algorithms, strategies, techniques can be used for the development of the cyberspace environment such as: cloud computing services; cyber security; data analytics; and, disruptive technologies like blockchain. The book presents new machine learning and data mining approaches in solving problems in cyber dynamics. Basic concepts, related work reviews, illustrations, empirical results and tables are integrated in each chapter to enable the reader to fully understand the concepts, methodology, and the results presented. The book contains empirical solutions of problems in cyber dynamics ready for industrial applications. The book will be an excellent starting point for postgraduate students and researchers because each chapter is design to have future research directions.

Encyclopedia of Machine Learning

Author : Claude Sammut
Publisher : Springer Science & Business Media
ISBN 13 : 0387307680
Total Pages : 1061 pages
Book Rating : 4.3/5 (873 download)

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Book Synopsis Encyclopedia of Machine Learning by : Claude Sammut

Download or read book Encyclopedia of Machine Learning written by Claude Sammut and published by Springer Science & Business Media. This book was released on 2011-03-28 with total page 1061 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive encyclopedia, in A-Z format, provides easy access to relevant information for those seeking entry into any aspect within the broad field of Machine Learning. Most of the entries in this preeminent work include useful literature references.

Data Mining

Author :
Publisher : BoD – Books on Demand
ISBN 13 : 1839692669
Total Pages : 226 pages
Book Rating : 4.8/5 (396 download)

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Book Synopsis Data Mining by :

Download or read book Data Mining written by and published by BoD – Books on Demand. This book was released on 2022-03-30 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: The availability of big data due to computerization and automation has generated an urgent need for new techniques to analyze and convert big data into useful information and knowledge. Data mining is a promising and leading-edge technology for mining large volumes of data, looking for hidden information, and aiding knowledge discovery. It can be used for characterization, classification, discrimination, anomaly detection, association, clustering, trend or evolution prediction, and much more in fields such as science, medicine, economics, engineering, computers, and even business analytics. This book presents basic concepts, ideas, and research in data mining.

Data Mining Applications with R

Author : Yanchang Zhao
Publisher : Academic Press
ISBN 13 : 0124115209
Total Pages : 514 pages
Book Rating : 4.1/5 (241 download)

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Book Synopsis Data Mining Applications with R by : Yanchang Zhao

Download or read book Data Mining Applications with R written by Yanchang Zhao and published by Academic Press. This book was released on 2013-11-26 with total page 514 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining Applications with R is a great resource for researchers and professionals to understand the wide use of R, a free software environment for statistical computing and graphics, in solving different problems in industry. R is widely used in leveraging data mining techniques across many different industries, including government, finance, insurance, medicine, scientific research and more. This book presents 15 different real-world case studies illustrating various techniques in rapidly growing areas. It is an ideal companion for data mining researchers in academia and industry looking for ways to turn this versatile software into a powerful analytic tool. R code, Data and color figures for the book are provided at the RDataMining.com website. Helps data miners to learn to use R in their specific area of work and see how R can apply in different industries Presents various case studies in real-world applications, which will help readers to apply the techniques in their work Provides code examples and sample data for readers to easily learn the techniques by running the code by themselves

Industrial Applications of Machine Learning

Author : Pedro Larrañaga
Publisher : CRC Press
ISBN 13 : 135112837X
Total Pages : 336 pages
Book Rating : 4.3/5 (511 download)

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Book Synopsis Industrial Applications of Machine Learning by : Pedro Larrañaga

Download or read book Industrial Applications of Machine Learning written by Pedro Larrañaga and published by CRC Press. This book was released on 2018-12-12 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Industrial Applications of Machine Learning shows how machine learning can be applied to address real-world problems in the fourth industrial revolution, and provides the required knowledge and tools to empower readers to build their own solutions based on theory and practice. The book introduces the fourth industrial revolution and its current impact on organizations and society. It explores machine learning fundamentals, and includes four case studies that address a real-world problem in the manufacturing or logistics domains, and approaches machine learning solutions from an application-oriented point of view. The book should be of special interest to researchers interested in real-world industrial problems. Features Describes the opportunities, challenges, issues, and trends offered by the fourth industrial revolution Provides a user-friendly introduction to machine learning with examples of cutting-edge applications in different industrial sectors Includes four case studies addressing real-world industrial problems solved with machine learning techniques A dedicated website for the book contains the datasets of the case studies for the reader's reproduction, enabling the groundwork for future problem-solving Uses of three of the most widespread software and programming languages within the engineering and data science communities, namely R, Python, and Weka

Machine Learning for Data Science Handbook

Author : Lior Rokach
Publisher : Springer Nature
ISBN 13 : 3031246284
Total Pages : 975 pages
Book Rating : 4.0/5 (312 download)

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Book Synopsis Machine Learning for Data Science Handbook by : Lior Rokach

Download or read book Machine Learning for Data Science Handbook written by Lior Rokach and published by Springer Nature. This book was released on 2023-08-17 with total page 975 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book organizes key concepts, theories, standards, methodologies, trends, challenges and applications of data mining and knowledge discovery in databases. It first surveys, then provides comprehensive yet concise algorithmic descriptions of methods, including classic methods plus the extensions and novel methods developed recently. It also gives in-depth descriptions of data mining applications in various interdisciplinary industries.