Temporal Data Mining via Unsupervised Ensemble Learning

Temporal Data Mining via Unsupervised Ensemble Learning
  • Author : Yun Yang
  • Publisher : Elsevier
  • Release : 15 November 2016
GET THIS BOOKTemporal Data Mining via Unsupervised Ensemble Learning

Temporal Data Mining via Unsupervised Ensemble Learning provides the principle knowledge of temporal data mining in association with unsupervised ensemble learning and the fundamental problems of temporal data clustering from different perspectives. By providing three proposed ensemble approaches of temporal data clustering, this book presents a practical focus of fundamental knowledge and techniques, along with a rich blend of theory and practice. Furthermore, the book includes illustrations of the proposed approaches based on data and simulation experiments to demonstrate all

Computational Intelligence and Its Applications

Computational Intelligence and Its Applications
  • Author : Abdelmalek Amine,Malek Mouhoub,Otmane Ait Mohamed,Bachir Djebbar
  • Publisher : Springer
  • Release : 26 April 2018
GET THIS BOOKComputational Intelligence and Its Applications

This book constitutes the refereed proceedings of the 6th IFIP TC 5 International Conference on Computational Intelligence and Its Applications, CIIA 2018, held in Oran, Algeria, in May 2018. The 56 full papers presented were carefully reviewed and selected from 202 submissions. They are organized in the following topical sections: data mining and information retrieval; evolutionary computation; machine learning; optimization; planning and scheduling; wireless communication and mobile computing; Internet of Things (IoT) and decision support systems; pattern recognition and image processing; and semantic web services.

Meta-Analytics

Meta-Analytics
  • Author : Steven Simske
  • Publisher : Morgan Kaufmann
  • Release : 10 March 2019
GET THIS BOOKMeta-Analytics

Meta-Analytics: Consensus Approaches and System Patterns for Data Analysis presents an exhaustive set of patterns for data science to use on any machine learning based data analysis task. The book virtually ensures that at least one pattern will lead to better overall system behavior than the use of traditional analytics approaches. The book is ‘meta’ to analytics, covering general analytics in sufficient detail for readers to engage with, and understand, hybrid or meta- approaches. The book has relevance to machine

Telematics and Computing

Telematics and Computing
  • Author : Miguel Felix Mata-Rivera,Roberto Zagal-Flores,Cristian Barría-Huidobro
  • Publisher : Springer Nature
  • Release : 24 October 2019
GET THIS BOOKTelematics and Computing

This book constitutes the thoroughly refereed proceedings of the 8th International Congress on Telematics and Computing, WITCOM 2019, held in Merida, Mexico, in November 2019. The 31 full papers presented in this volume were carefully reviewed and selected from 78 submissions. The papers are organized in topical sections: ​GIS & climate change; telematics & electronics; artificial intelligence & machine learning; software engineering & education; internet of things; and informatics security.

Fault Diagnosis, Prognosis, and Reliability for Electrical Machines and Drives

Fault Diagnosis, Prognosis, and Reliability for Electrical Machines and Drives
  • Author : Elias G. Strangas,Guy Clerc,Hubert Razik,Abdenour Soualhi
  • Publisher : John Wiley & Sons
  • Release : 19 November 2021
GET THIS BOOKFault Diagnosis, Prognosis, and Reliability for Electrical Machines and Drives

Fault Diagnosis, Prognosis, and Reliability for Electrical Machines and Drives An insightful treatment of present and emerging technologies in fault diagnosis and failure prognosis In Fault Diagnosis, Prognosis, and Reliability for Electrical Machines and Drives, a team of distinguished researchers delivers a comprehensive exploration of current and emerging approaches to fault diagnosis and failure prognosis of electrical machines and drives. The authors begin with foundational background, describing the physics of failure, the motor and drive designs and components that affect

Practical Machine Learning for Data Analysis Using Python

Practical Machine Learning for Data Analysis Using Python
  • Author : Abdulhamit Subasi
  • Publisher : Academic Press
  • Release : 05 June 2020
GET THIS BOOKPractical Machine Learning for Data Analysis Using Python

Practical Machine Learning for Data Analysis Using Python is a problem solver’s guide for creating real-world intelligent systems. It provides a comprehensive approach with concepts, practices, hands-on examples, and sample code. The book teaches readers the vital skills required to understand and solve different problems with machine learning. It teaches machine learning techniques necessary to become a successful practitioner, through the presentation of real-world case studies in Python machine learning ecosystems. The book also focuses on building a foundation

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 BOOKNature-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

Temporal Data Mining

Temporal Data Mining
  • Author : Theophano Mitsa
  • Publisher : CRC Press
  • Release : 10 March 2010
GET THIS BOOKTemporal Data Mining

Temporal data mining deals with the harvesting of useful information from temporal data. New initiatives in health care and business organizations have increased the importance of temporal information in data today. From basic data mining concepts to state-of-the-art advances, Temporal Data Mining covers the theory of this subject as well as its application in a variety of fields. It discusses the incorporation of temporality in databases as well as temporal data representation, similarity computation, data classification, clustering, pattern discovery, and

Machine Learning and Data Mining in Pattern Recognition

Machine Learning and Data Mining in Pattern Recognition
  • Author : Petra Perner,Azriel Rosenfeld
  • Publisher : Springer
  • Release : 02 August 2003
GET THIS BOOKMachine 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

Recording Science in the Digital Era

Recording Science in the Digital Era
  • Author : Cerys Willoughby
  • Publisher : Royal Society of Chemistry
  • Release : 15 July 2019
GET THIS BOOKRecording Science in the Digital Era

For most of the history of scientific endeavour, science has been recorded on paper. In this digital era, however, there is increasing pressure to abandon paper in favour of digital tools. Despite the benefits, there are barriers to the adoption of such tools, not least their usability. As the relentless development of technology changes the way we work, we need to ensure that the design of technology not only overcomes these barriers, but facilitates us as scientists and supports better

Applications and Techniques in Information Security

Applications and Techniques in Information Security
  • Author : V. S. Shankar Sriram,V. Subramaniyaswamy,N. Sasikaladevi,Leo Zhang,Lynn Batten,Gang Li
  • Publisher : Springer Nature
  • Release : 15 November 2019
GET THIS BOOKApplications and Techniques in Information Security

This book constitutes the refereed proceedings of the 10th International Conference on Applications and Techniques in Information Security, ATIS 2019, held in Tamil Nadul, India, in November 2019. The 22 full papers and 2 short papers presented in the volume were carefully reviewed and selected from 50 submissions. The papers are organized in the following topical sections: information security; network security; intrusion detection system; authentication and key management system; security centric applications.