Recent Developments in Machine Learning and Data Analytics [electronic resource] : IC3 2018 /
Kalita, Jugal.editor.
Balas, Valentina Emilia.editor.
Borah, Samarjeet.editor.
Pradhan, Ratika.editor.
This book presents high-quality papers from an international forum for research on computational approaches to learning. It includes current research and findings from various research labs, universities and institutions that may lead to development of marketable products. It also provides solid support for these findings in the form of empirical studies, theoretical analysis, or comparison to psychological phenomena. Further, it features work that shows how to apply learning methods to solve important application problems as well as how machine learning research is conducted. The book is divided into two main parts: Machine Learning Techniques, which covers machine learning-related research and findings; and, Data Analytics, which introduces recent developments in this domain. Additionally, the book includes work on data analytics using machine learning techniques. .
Chapter 1: MaNaDAC:An Effective Alert Correlation Method -- Chapter 2: WSD for Assamese Language -- Chapter 3: Fuzzy Clustering with Ensemble Classiﬁcation techniques to improve the Customer Churn Prediction in Telecommunication Sector -- Chapter 4: Interval-valued complex fuzzy concept lattice and its granular decomposition -- Chapter 5: SBFP-growth: A Step to remove the bottleneck of FP-tree -- Chapter 6: Combining Multi-level Contexts of Superpixel using Convolutional Neural Networks to perform Natural Scene Labeling -- Chapter 7: A fast Algorithm for Automatic Segmentation of Pancreas Histological Images for Glucose Intolerance Identification -- Chapter 8: Aptitude Question Paper Generator and Answer Verification System -- Chapter 9: Elephant Herding Algorithm for Clustering -- Chapter 10: Affinity Maturation of Homophones in Word-Level Speech Recognition -- Chapter 11: Fusion based Underwater Image Enhancement by Weight Map Techniques -- Chapter 12: IoT Enabled Ubiquitous Healthcare Data Acquisition and Monitoring System for Personal and Medical usage Powered by Cloud Application: An Architectural Overview -- Chapter 13: Analysis and Prediction of City Scale Transportation System Using XGBOOST Technique -- Chapter 14: Sensor Selection and Data Fusion Approach for IoT Applications -- Chapter 15: An overview of Hadoop Mapreduce, Spark and Scala-ble Graph Processing Architecture -- Chapter 16: Analyzing Social Trend towards Girl Child in India: A Machine Intelligence based Approach.
This book presents high-quality papers from an international forum for research on computational approaches to learning. It includes current research and findings from various research labs, universities and institutions that may lead to development of marketable products. It also provides solid support for these findings in the form of empirical studies, theoretical analysis, or comparison to psychological phenomena. Further, it features work that shows how to apply learning methods to solve important application problems as well as how machine learning research is conducted. The book is divided into two main parts: Machine Learning Techniques, which covers machine learning-related research and findings; and, Data Analytics, which introduces recent developments in this domain. Additionally, the book includes work on data analytics using machine learning techniques. .
Engineering.
Data mining.
Computer vision.
Computational Intelligence.
Data Mining and Knowledge Discovery.
Image Processing and Computer Vision.