Data Classification and Incremental Clustering in Data Mining and Machine Learning - Sanjay Chakraborty, SK Hafizul Islam, Debabrata Samanta

Data Classification and Incremental Clustering in Data Mining and Machine Learning

Buch | Softcover
XXI, 196 Seiten
2023 | 1st ed. 2022
Springer International Publishing (Verlag)
978-3-030-93090-5 (ISBN)
85,59 inkl. MwSt
This book is a comprehensive, hands-on guide to the basics of data mining and machine learning with a special emphasis on supervised and unsupervised learning methods. The book lays stress on the new ways of thinking needed to master in machine learning based on the Python, R, and Java programming platforms. This book first provides an understanding of data mining, machine learning and their applications, giving special attention to classification and clustering techniques. The authors offer a discussion on data mining and machine learning techniques with case studies and examples. The book also describes the hands-on coding examples of some well-known supervised and unsupervised learning techniques using three different and popular coding platforms: R, Python, and Java. This book explains some of the most popular classification techniques (K-NN, Naïve Bayes, Decision tree, Random forest, Support vector machine etc,) along with the basic description of artificial neural network and deep neural network. The book is useful for professionals, students studying data mining and machine learning, and researchers in supervised and unsupervised learning techniques.

lt;p>Sanjay Chakraborty is currently an Assistant Professor of the Department of Computer Science and Engineering, JIS University, Kolkata, India. He did his B-Tech from West Bengal University of Technology, India on Information Technology in the year 2009. He completed his Master of Technology (M-Tech) from National Institute of Technology, Raipur, India in the year of 2011. He has submitted his Ph.D. thesis at AKCSIT, University of Calcutta in 2020. Mr. Chakraborty is the recipient of the University Silver Medal from NIT Raipur in 2011 for ranking first-class second in M-Tech. He has 10+ years of teaching and research experience. He has published over 50 research papers in various international journals, conferences, and book chapters. He is the author of one book on ML-based Brain-computer interfacing published by Lap Lambert, Germany. Mr. Chakraborty attended many national and international conferences in India and abroad. His research interests include Data Mining & Machine Learning and Quantum Computing. He is a professional member of IAENG and UACEE. Mr. Chakraborty is an active member of the board of reviewers in various International Journals and Conferences. He is the recipient of "INNOVATION AWARD" for outstanding achievement in the field of Innovation by Techno India Institution's Innovation Council 2019. He is also the recipient of "IEEE Young Professional Best Paper Award" in 2017. He has also achieved the top five best paper recognition by Ain Shams Engineering Journal, Elsevier. He is a reviewer of various IEEE transactions, Nature, and other reputed journals and conferences.

SK Hafizul Islam received the M.Sc. degree in Applied Mathematics from Vidyasagar University, Midnapore, India, in 2006, and the M.Tech. degree in Computer Application and the Ph.D. degree in Computer Science and Engineering in 2009 and 2013, respectively, from the Indian Institute of Technology [IIT (ISM)] Dhanbad, Jharkhand, India, under the INSPIRE Fellowship Ph.D. Program (funded by Department of Science and Technology, Government of India). He is currently an Assistant Professor with the Department of Computer Science and Engineering, Indian Institute of Information Technology Kalyani (IIIT Kalyani), West Bengal, India. Before joining the IIIT Kalyani, he was an Assistant Professor with the Department of Computer Science and Information Systems, Birla Institute of Technology and Science, Pilani (BITS Pilani), Rajasthan, India. He has more than eight years of teaching and ten years of research experiences. He has authored or co-authored hundred research papers in journals and conference proceedings of international reputes. His research interests include cryptography, information security, WSNs, IoT, and cloud computing. Dr. Islam is an Associate Editor for Wiley's "International Journal of Communication Systems" and "Security and Privacy" and IEEE's "IEEE Access". He was a reviewer in many reputed international journals and conferences. He was the recipient of the University Gold Medal, the S. D. Singha Memorial Endowment Gold Medal, and the Sabitri Parya Memorial Endowment Gold Medal from Vidyasagar University, in 2006. He was also the recipient of the University Gold Medal from IIT(ISM) Dhanbad in 2009 and the OPERA award from BITS Pilani in 2015. He is a senior member of the IEEE and a member of the ACM.

 

Dr. Debabrata Samanta is presently working as Assistant Professor, Department of Computer Science, CHRIST (Deemed to be University), Bangalore, India. He obtained his Bachelors in Physics (Honors), from Calcutta University; Kolkata, India. He obtained his MCA, from the Academy of Technology, under WBUT, West Bengal. He obtained his PhD in Computer Science and Engg. from National Institute of Technology, Durgapur, India, in the area of SAR Image Processing. He is keenly interested in Interdisciplinary Research & Development and has experience spanning fields of SAR Imag

Introduction to Data Mining & Knowledge Discovery.- A Brief Concept on Machine Learning.- Supervised Learning based Data Classification and Incremental Clustering.- Data Classification and Incremental Clustering using Unsupervised Learning.- Research Intention towards Incremental Clustering.- Applications and Trends in Data Mining & Machine Learning.- Feature subset selection techniques with Machine Learning.- Data Mining Based variant subsets features.

Erscheinungsdatum
Reihe/Serie EAI/Springer Innovations in Communication and Computing
Zusatzinfo XXI, 196 p. 86 illus., 42 illus. in color.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Gewicht 343 g
Themenwelt Technik Elektrotechnik / Energietechnik
Technik Nachrichtentechnik
Schlagworte classification • Clustering • Data Mining • machine learning • supervised learning • Unsupervised Learning
ISBN-10 3-030-93090-4 / 3030930904
ISBN-13 978-3-030-93090-5 / 9783030930905
Zustand Neuware
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