Applications of Machine Learning

1. Front Matter

   Pages i-xxii

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2. Statistical Learning Process for the Reduction of Sample Collection Assuring a Desired Level of Confidence

   • Vicente González-Prida, Jesús Zamora, Adolfo Crespo, Pedro Moreu

   Pages 1-14

3. Sentiment Analysis on Google Play Store Data Using Deep Learning

   • Swathi Venkatakrishnan, Abhishek Kaushik, Jitendra Kumar Verma

   Pages 15-30

4. Managing the Data Meaning in the Data Stream Processing: A Systematic Literature Mapping

   • Mario José Diván, María Laura Sánchez-Reynoso

   Pages 31-46

5. Tracking an Object Using Traditional MS (Mean Shift) and CBWH MS (Mean Shift) Algorithm with Kalman Filter

   • Sandeep Kumar, Rohit Raja, Archana Gandham

   Pages 47-65

6. Transfer Learning and Domain Adaptation for Named-Entity Recognition

   • Raghul Prakash, Rahul Kumar Dubey

   Pages 67-73

7. Knowledge Graph from Informal Text: Architecture, Components, Algorithms and Applications

   • Anmol Nayak, Vaibhav Kesri, Rahul K. Dubey, Sarathchandra Mandadi, Vijendran G. Venkoparao, Karthikeyan Ponnalagu et al.

   Pages 75-90

8. Neighborhood-Based Collaborative Recommendations: An Introduction

   • Vijay Verma, Rajesh Kumar Aggarwal

   Pages 91-110

9. Classification of Arabic Text Using Singular Value Decomposition and Fuzzy C-Means Algorithms

   • Ahmad T. Al-Taani, Sami H. Al-Sayadi

   Pages 111-123

10. Echo State Network Based Nonlinear Channel Equalization in Wireless Communication System

    • Saikat Majumder

    Pages 125-139

11. Melody Extraction from Music: A Comprehensive Study

    • Ranjeet Kumar, Anupam Biswas, Pinki Roy

    Pages 141-155

12. Comparative Analysis of Combined Gas Turbine–Steam Turbine Power Cycle Performance by Using Entropy Generation and Statistical Methodology

    • Kaushalendra Kumar Dubey, R. S. Mishra

    Pages 157-175

13. Data Mining—A Tool for Handling Huge Voluminous Data

    • Seema Maitrey, Yogesh Kumar Gupta

    Pages 177-188

14. Improving the Training Pattern in Back-Propagation Neural Networks Using Holt-Winters’ Seasonal Method and Gradient Boosting Model

    • S. Brilly Sangeetha, N. R. Wilfred Blessing, N. Yuvaraj, J. Adeline Sneha

    Pages 189-198

15. Ensemble of Multi-headed Machine Learning Architectures for Time-Series Forecasting of Healthcare Expenditures

    • Shruti Kaushik, Abhinav Choudhury, Nataraj Dasgupta, Sayee Natarajan, Larry A. Pickett, Varun Dutt

    Pages 199-216

16. Soft Computing Approaches to Investigate Software Fault Proneness in Agile Software Development Environment

    • Pooja Sharma, Amrit Lal Sangal

    Pages 217-233

17. Week Ahead Time Series Prediction of Sea Surface Temperature Using Nonlinear Autoregressive Network with and Without Exogenous Inputs

    • Geetali Saha, N. C. Chauhan

    Pages 235-256

18. Regression Model of Frame Rate Processing Performance for Embedded Systems Devices

    • Yaroslav Krainyk

    Pages 257-265

19. Time Series Data Representation and Dimensionality Reduction Techniques

    • Anshul Sharma, Abhinav Kumar, Anil Kumar Pandey, Rishav Singh

    Pages 267-284

20. Simultaneous Localization and Mapping with Gaussian Technique

    • Sai Prabanjan Kumar Kalvapalli, C. Mala

    Pages 285-291

This book covers applications of machine learning in artificial intelligence. The specific topics covered include human language, heterogeneous and streaming data, unmanned systems, neural information processing, marketing and the social sciences, bioinformatics and robotics, etc. It also provides a broad range of techniques that can be successfully applied and adopted in different areas. Accordingly, the book offers an interesting and insightful read for scholars in the areas of computer vision, speech recognition, healthcare, business, marketing, and bioinformatics.

• Fuzyy Logic
• Neural Networks
• Evolutionary Computation
• Learning Theory
• Probabilistic Methods
• Telemedicine and Robotics
• Artificial Intelligence
• Soft Computing
• Image Processing

• School of Computer Science and Engineering, Galgotias University, Greater Noida, India

  Prashant Johri

• Department of Computer Science and Engineering, Amity School of Engineering and Technology, Amity University Haryana, Gurugram (Manesar), India

  Jitendra Kumar Verma

• Department of Biomedical Engineering, North-Eastern Hill University, Shillong, India

  Sudip Paul

Dr. Prashant Johri is a Professor at the School of Computing Science & Engineering, Galgotias University, Greater Noida, India. He received his MCA from Aligarh Muslim University and Ph.D. in Computer Science from Jiwaji University, Gwalior, India. He has also worked as a Professor and Director (MCA), Noida Institute of Engineering and Technology, (NIET). His research interests include big data, data analytics, data retrieval and predictive analytics, information security, privacy protection, big data open platforms, etc. He is actively publishing in these areas.




Dr. Jitendra Kumar Verma is Assistant Professor (Grade III) of Computer Science & Engineering at Amity School of Engineering & Technology, Amity University Haryana, Gurugram (Manesar), India. He received the degree of Ph.D. from Jawaharlal Nehru University (JNU), New Delhi, India in 2017, degree of M.Tech from JNU in 2013 and degree of B.Tech in Computer Science & Engineering from Kamla Nehru Institute of Technology (KNIT), Sultanpur, Uttar Pradesh, India in 2008. Dr. Verma is awardee of prestigious DAAD "A new Passage to India" Fellowship (2015-16) funded by Federal Ministry of Education and Research - BMBF, Germany and German Academic Exchange Service (DAAD). He worked at JULIUS-MAXIMILIAN UNIVERSITY OF WÜRZBURG, GERMANY (mother of 14 Nobel Laureate) as a Visiting Research Scholar. Dr. Verma is member of several technical societies e.g. IEEE, IEEE IAS, and ACM. Over his short career, he published several research papers in proceedings of various international conferences and peer-reviewed International Journals of repute. He also contributed numerous book chapters to the several books published with publishers of high international repute. Apart from scholarly contribution towards scientific community, he organized several Conferences/Workshops/Seminars at the national and international levels. He voluntarily served as reviewer for various International Journals, conferences, and workshops. He also served as Guest Editor and Editorial Board Member of numerous international journals.  His research interest includes cloud computing, Mobile cloud, Machine learning, AR & VR, Soft computing, Fuzzy systems, Healthcare, Pattern recognition, Bio-inspired phenomena, and advanced optimization model & computation.



Dr. Sudip Paul is an Assistant Professor at the Department of Biomedical Engineering, School of Technology, North-Eastern Hill University (NEHU), Shillong, India. He received his Ph.D. from the Indian Institute of Technology (Banaras Hindu University), Varanasi, with a specialization in Electrophysiology and Brain Signal Analysis. He was selected as a Postdoc Fellow in 2017–18 under the Biotechnology Overseas Associateship for scientists working in the Northeastern States of India, supported by the Department of Biotechnology, Government of India. Dr. Sudip has published morethan 90 international journal and conference papers and has filed four patents. Recently, he completed three book projects and is currently serving as Editor for a further two. Dr. Sudip is a member of numerous societies and professional bodies, e.g. the APSN, ISN, IBRO, SNCI, SfN, and IEEE. He received First Prize in the Sushruta Innovation Award 2011, sponsored by the Department of Science and Technology, Government of India, and various other awards, including a World Federation of Neurology (WFN) Travelling Fellowship, Young Investigator Award, and IBRO and ISN Travel Awards. Dr. Sudip has also served as an editorial board member for a variety of international journals.

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