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Group Method of Data Handling: How Does it Measure Up?

Authors:
Poorani Selvaraj
Gary Weckman
Andrew Snow

Keywords: Group Method of Data Handling; Artificial Neural Networks; Prediction; Statistics; Feature Selection

Abstract:
Prediction is the method of determining future values based on the patterns deduced from a data set. This research compares various data mining techniques—namely, multiple regression analysis in statistics, Artificial Neural Networks (ANN), and the Group Method of Data Handling (GMDH), including both with and without feature selection. Currently, the literature suggests that GMDH, an inductive learning algorithm, is an excellent tool for prediction. GMDH builds gradually more complex models that are evaluated via a set of multi-input, single-output data pairs. ANNs are inspired by the complex learning that happens in the closely interconnected sets of neurons in the human brain and are also considered an excellent tool for prediction. This article is the beginning of a more detailed research project to investigate how well GMDH performs in comparison to other data mining tools.

Pages: 108 to 113

Copyright: Copyright (c) IARIA, 2016

Publication date: February 21, 2016

Published in: conference

ISSN: 2519-8386

ISBN: 978-1-61208-457-2

Location: Lisbon, Portugal

Dates: from February 21, 2016 to February 25, 2016