Improving Classifier Generalization: Real-Time Machine Learning based Applications (Studies in Computational Intelligence, 989) free ebook download.

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Improving Classifier Generalization: Real-Time Machine Learning based Applications (Studies in Computational Intelligence, 989) free ebook download

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Catalogue

Author(s):	Rahul Kumar Sevakula

Date:	2021	Format:	pdf	Language:	English	ISBN/ASIN:	9811950725
Pages:	189	OCR:		Quality:		ISBN13:
Uploader:	risotor	Upload Date:	8/13/2023 11:28:42 PM

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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: ranging from datasets of UCI repository to predictive maintenance problems and cancer classification problems. The book specifically provides a detailed tutorial on how to approach time-series classification problems and discusses two real time 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, time-series analysis, gene-expression data classification.

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3195206	Book	https://rapidgator.net/file/3fc03f687efb...		0.00	risotor

Tags: Applications based Classifier Computational Generalization Improving Learning Machine Real-Time Studies

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