Data Classification: Algorithms and Applications

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How researchers see this paper

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Visualizing Big Data with augmented and virtual reality: challenges and research agenda (2015, background): “Classification [80] is a set of techniques which are”
Feature Selection (2016, background): “Currently, there exist a number of surveys about feature selection algorithms (Guyon and Elisseeff, 2003; Alelyani et al., 2013; Chandrashekar and Sahin, 2014; Tang et al., 2014).”
Star-galaxy Classification Using Deep Convolutional Neural Networks (2016, methodology): “An artificial neuron in most artificial neural networks is represented as a mathematical function that models a biological neural structure (Aggarwal 2014).”
Constructing effective personalized policies using counterfactual inference from biased data sets with many features (2016, methodology): “With respect to learning, feature selection methods can be divided into three categories – ﬁlter models, wrapper models, and embedded models [Tang et al(2014)].”
Supervised, Unsupervised, and Semi-Supervised Feature Selection: A Review on Gene Selection (2016, background): “Even though there are a lot of review papers on gene selection in the literatures [4], [5], [6], [7], [8], but to the best of our knowledge, there is no detailed discussion on the methods and separates them in such three categories as in this paper.”