Titlebook: Machine Learning Paradigms; Applications of Lear George A. Tsihrintzis,Maria Virvou,Lakhmi C. Jain Book 2019 Springer Nature Switzerland AG

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2662-3447 research on machine learning paradigms.Written by recognized.This book is the inaugural volume in the new Springer series on .Learning and Analytics in Intelligent Systems.. The series aims at providing, in hard-copy and soft-copy form, books on all aspects of learning, analytics, advanced intellige

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Book 2019 the series will publish edited books, monographs, handbooks, textbooks and conference proceedings. This book is intended for professors, researchers, scientists, engineers and students. An extensive list of references at the end of each chapter allows readers to probe further into those application areas that interest them most. .

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Automated Stock Price Motion Prediction Using Technical Analysis Datasets and Machine Learningattempt to generalize the model for all stocks would make our effort impossible. A use case with the famous US S&P 500 index has been also tested. We conclude with a discussion on the optimization of the accuracy of such systems.

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A Comparison of Machine Learning Techniques to Predict the Risk of Heart Failurea comparison of the different techniques used to find the best performance. A conclusion of the best technique is also provided in this chapter. Some examples of the techniques are C4.5 tree, Naïve Bayes, Bayesian Neural Networks (BNN), Support Vector Machine (SVM), Artificial Neural Network (ANN), Nearest Neighbor (KNN).

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Differential Gene Expression Analysis of RNA-seq Data Using Machine Learning for Cancer Research the understanding of complex, multi-factorial and heterogeneous diseases such as cancer. Profiling of transcriptome is used for searching the genes that show differences in their expression level associated with a particular response. RNA-seq data allows researchers to study millions of short reads