Titlebook: Supervised and Unsupervised Learning for Data Science; Michael W. Berry,Azlinah Mohamed,Bee Wah Yap Book 2020 Springer Nature Switzerland

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Survival Support Vector Machines: A Simulation Study and Its Health-Related Applicationn is employed utilizing a concordance index increment. Moreover, the simulation study was conducted to know the effect of the number of features, sample size, and censoring percentage on the performance of the SURLS-SVM.

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2522-848X ture extraction and selection using semi-supervised and unsu.This book covers the state of the art in learning algorithms with an inclusion of semi-supervised methods to provide a broad scope of clustering and classification solutions for big data applications. Case studies and best practices are in

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A Systematic Review on Supervised and Unsupervised Machine Learning Algorithms for Data Science to analyze scholarly articles that were published between 2015 and 2018 addressing or implementing supervised and unsupervised machine learning techniques in different problem-solving paradigms. Using the elements of PRISMA, the review process identified 84 scholarly articles that had been publishe

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Overview of One-Pass and Discard-After-Learn Concepts for Classification and Clustering in Streamingain valuable and possibly relevant information for various fields of applications. Learning these data online by using current neural learning techniques is not so simple due to many technical constraints including data overflow, uncontrollable learning epochs, arbitrary class drift, and dynamic imb

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Distributed Single-Source Shortest Path Algorithms with Two-Dimensional Graph Layoutgraph analytical analyses in many research areas such as networks, communication, transportation, electronics, and so on. In this chapter, we propose scalable SSSP algorithms for distributed memory systems. Our algorithms are based on a ∆-stepping algorithm with the use of a two-dimensional (2D) gra

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Using Non-negative Tensor Decomposition for Unsupervised Textual Influence Modeling, or documents which authors have read. This influence can be seen within their works, and is present as a latent variable. This chapter demonstrates a novel method for quantifying these influences and representing them in a semantically understandable fashion. The model is constructed by representi