Online Feature Selection for Streaming Features Using Self-Adaption Sliding-Window Sampling
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DOI: 10.1109/access.2019.2894121
Abstract: In recent years, online feature selection has been a research topic on streaming feature mining, as it can reduce the dimensionality of the streaming features by removing the irrelevant and redundant features in real time.… read more here.
Keywords: streaming features; online feature; feature selection; prediction accuracy ... See more keywords
Extensions to Online Feature Selection Using Bagging and Boosting
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DOI: 10.1109/tnnls.2017.2746107
Abstract: Feature subset selection can be used to sieve through large volumes of data and discover the most informative subset of variables for a particular learning problem. Yet, due to memory and other resource constraints (e.g.,… read more here.
Keywords: feature selection; feature; online feature; selection ... See more keywords
Online Feature Selection (OFS) with Accelerated Bat Algorithm (ABA) and Ensemble Incremental Deep Multiple Layer Perceptron (EIDMLP) for big data streams
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Big Data"
DOI: 10.1186/s40537-019-0267-3
Abstract: Feature selection is mainly used to lessen the dispensation load of data mining models. To condense the time for processing voluminous data, parallel processing is carried out with MapReduce (MR) technique. However with the existing… read more here.
Keywords: feature selection; feature; online feature; research work ... See more keywords