Improving Classifier Generalization: Real-Time Machine Learning based Applications (true EPUB)

[LeeAndro]

English | 2023 | ISBN: 9811950725 | 181 Pages | EPUB PDF (True) | 25 MB

This book elaborately discusses techniques commonly used to improve generalization performance in classification approaches.​

The contents highlight methods to improve classification performance in numerous case studies: rag from datasets of UCI repository to predictive maintenance problems and cancer classification problems. The book specifically provides a detailed tutorial on how to approach -series classification problems and discusses two real case studies on condition monitoring. In addition to describing the various aspects a data scientist must consider before finalizing their approach to a classification problem and reviewing the state of the art for improving classification generalization performance, it also discusses in detail the authors own contributions to the field, including MVPC - a classifier with very low VC dimension, a graphical indices based framework for reliable predictive maintenance and a novel general-purpose membership functions for Fuzzy Support Vector Machine which provides state of the art performance with noisy datasets, and a novel scheme to introduce deep learning in Fuzzy Rule based classifiers (FRCs). This volume will serve as a useful reference for researchers and students working on machine learning, health monitoring, predictive maintenance, -series analysis, gene-expression data classification.



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