Data Classification and Incremental Clustering in Data Mining and Machine Learning, Chakraborty Sanjay, Islam Sk Hafizul, Samanta Debabrata
Автор: Olfa Nasraoui; Chiheb-Eddine Ben N`Cir Название: Clustering Methods for Big Data Analytics ISBN: 3319978632 ISBN-13(EAN): 9783319978635 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book highlights the state of the art and recent advances in Big Data clustering methods and their innovative applications in contemporary AI-driven systems. The book chapters discuss Deep Learning for Clustering, Blockchain data clustering, Cybersecurity applications such as insider threat detection, scalable distributed clustering methods for massive volumes of data; clustering Big Data Streams such as streams generated by the confluence of Internet of Things, digital and mobile health, human-robot interaction, and social networks; Spark-based Big Data clustering using Particle Swarm Optimization; and Tensor-based clustering for Web graphs, sensor streams, and social networks. The chapters in the book include a balanced coverage of big data clustering theory, methods, tools, frameworks, applications, representation, visualization, and clustering validation.
Автор: Alejandro Dizan Vasquez Govea Название: Incremental Learning for Motion Prediction of Pedestrians and Vehicles ISBN: 3642263852 ISBN-13(EAN): 9783642263859 Издательство: Springer Рейтинг: Цена: 104480.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book focuses on the problem of moving in a cluttered environment with pedestrians and vehicles. A framework based on Hidden Markov models is developed to learn typical motion patterns which can be used to predict motion on the basis of sensor data.
Автор: Haym Hirsh Название: Incremental Version-Space Merging: A General Framework for Concept Learning ISBN: 0792391195 ISBN-13(EAN): 9780792391197 Издательство: Springer Рейтинг: Цена: 121110.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: One of the most enjoyable experiences in science is hearing a simple but novel idea which instantly rings true, and whose consequences then begin to unfold in unforeseen directions. For me, this book presents such an idea and several of its ramifications. This book is concerned with machine learning. It focuses on a ques- tion that is central to understanding how computers might learn: "how can a computer acquire the definition of some general concept by abstracting from specific training instances of the concept?" Although this question of how to automatically generalize from examples has been considered by many researchers over several decades, it remains only partly answered. The approach developed in this book, based on Haym Hirsh's Ph.D. dis- sertation, leads to an algorithm which efficiently and exhaustively searches a space of hypotheses (possible generalizations of the data) to find all maxi- mally consistent hypotheses, even in the presence of certain types of incon- sistencies in the data. More generally, it provides a framework for integrat- ing different types of constraints (e.g., training examples, prior knowledge) which allow the learner to reduce the set of hypotheses under consideration.
Автор: Alejandro Dizan Vasquez Govea Название: Incremental Learning for Motion Prediction of Pedestrians and Vehicles ISBN: 3642136419 ISBN-13(EAN): 9783642136412 Издательство: Springer Рейтинг: Цена: 121890.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book focuses on the problem of moving in a cluttered environment with pedestrians and vehicles. A framework based on Hidden Markov models is developed to learn typical motion patterns which can be used to predict motion on the basis of sensor data.
Автор: Haym Hirsh Название: Incremental Version-Space Merging: A General Framework for Concept Learning ISBN: 1461288347 ISBN-13(EAN): 9781461288343 Издательство: Springer Рейтинг: Цена: 107130.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: dis- sertation, leads to an algorithm which efficiently and exhaustively searches a space of hypotheses (possible generalizations of the data) to find all maxi- mally consistent hypotheses, even in the presence of certain types of incon- sistencies in the data.
Автор: V.S. Kumbhar, K.S. Oza, R.K. Kamat Название: Web Mining: A Synergic Approach Resorting to Classification and Clustering ISBN: 8793379838 ISBN-13(EAN): 9788793379831 Издательство: Taylor&Francis Рейтинг: Цена: 73490.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Showcases an effective methodology for classification and clustering of web sites from a usability point of view. While the clustering and classification is accomplished by using an open source tool, WEKA, the basic dataset for the selected websites has been arrived at by using a free tool site-analyser. As a case study, several commercial websites are analysed.
Автор: Seetha Hari, Murty M. Narasimha, Tripathy B. K. Название: Modern Technologies for Big Data Classification and Clustering ISBN: 1522528059 ISBN-13(EAN): 9781522528050 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 208830.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Data has increased due to the growing use of web applications and communication devices. It is necessary to develop new techniques of managing data in order to ensure adequate usage.Modern Technologies for Big Data Classification and Clustering is an essential reference source for the latest scholarly research on handling large data sets with conventional data mining and provide information about the new technologies developed for the management of large data. Featuring coverage on a broad range of topics such as text and web data analytics, risk analysis, and opinion mining, this publication is ideally designed for professionals, researchers, and students seeking current research on various concepts of big data analytics.Topics Covered:The many academic areas covered in this publication include, but are not limited to:Data visualizationDistributed Computing SystemsOpinion MiningPrivacy and securityRisk analysisSocial Network AnalysisText Data AnalyticsWeb Data Analytics
Автор: Jin Cheqing, Zhou Aoying, Mao Jiali Название: Clustering And Outlier Detection For Trajectory Stream Data ISBN: 9811210454 ISBN-13(EAN): 9789811210457 Издательство: World Scientific Publishing Рейтинг: Цена: 95040.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
As mobile devices continue becoming a larger part of our lives, the development of location acquisition technologies to track moving objects have focused the minds of researchers on issues ranging from longitude and latitude coordinates, speed, direction, and timestamping, as part of parameters needed to calculate the positional information and locations of objects, in terms of time and position in the form of trajectory streams. Recently, recent advances have facilitated various urban applications such as smart transportation and mobile delivery services.
Unlike other books on spatial databases, mobile computing, data mining, or computing with spatial trajectories, this book is focused on smart transportation applications.
This book is a good reference for advanced undergraduates, graduate students, researchers, and system developers working on transportation systems.
Автор: Boris Mirkin Название: Mathematical Classification and Clustering ISBN: 146138057X ISBN-13(EAN): 9781461380573 Издательство: Springer Рейтинг: Цена: 111790.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The monograph is devoted entirely to clustering, a discipline dispersed through many theoretical and application areas, from mathematical statistics and combina- torial optimization to biology, sociology and organizational structures.
Автор: Surekha Borra; Rohit Thanki; Nilanjan Dey Название: Satellite Image Analysis: Clustering and Classification ISBN: 9811364230 ISBN-13(EAN): 9789811364235 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Thanks to recent advances in sensors, communication and satellite technology, data storage, processing and networking capabilities, satellite image acquisition and mining are now on the rise. In turn, satellite images play a vital role in providing essential geographical information. Highly accurate automatic classification and decision support systems can facilitate the efforts of data analysts, reduce human error, and allow the rapid and rigorous analysis of land use and land cover information. Integrating Machine Learning (ML) technology with the human visual psychometric can help meet geologists’ demands for more efficient and higher-quality classification in real time.
This book introduces readers to key concepts, methods and models for satellite image analysis; highlights state-of-the-art classification and clustering techniques; discusses recent developments and remaining challenges; and addresses various applications, making it a valuable asset for engineers, data analysts and researchers in the fields of geographic information systems and remote sensing engineering.
Автор: Saman K. Halgamuge; Lipo Wang Название: Classification and Clustering for Knowledge Discovery ISBN: 3642065422 ISBN-13(EAN): 9783642065422 Издательство: Springer Рейтинг: Цена: 194730.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book covers recent advances in unsupervised and supervised data analysis methods in Computational Intelligence for knowledge discovery. If labeled data or data with known associations are available, we may be able to use supervised data analysis methods, such as classifying neural networks, fuzzy rule-based classifiers, and decision trees.
Автор: Meera Ramadas; Ajith Abraham Название: Metaheuristics for Data Clustering and Image Segmentation ISBN: 3030040968 ISBN-13(EAN): 9783030040963 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: In this book, differential evolution and its modified variants are applied to the clustering of data and images. Metaheuristics have emerged as potential algorithms for dealing with complex optimization problems, which are otherwise difficult to solve using traditional methods. In this regard, differential evolution is considered to be a highly promising technique for optimization and is being used to solve various real-time problems. The book studies the algorithms in detail, tests them on a range of test images, and carefully analyzes their performance. Accordingly, it offers a valuable reference guide for all researchers, students and practitioners working in the fields of artificial intelligence, optimization and data analytics.
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