The effect of sample size and variability of data on the comparative performance of artificial neural networks and regression
Computers & Operations ResearchPublished 1 April 1998
Ina S. Markham, Terry R. Rakes
Citations102
SJR quartileQ1
SJR score1.60
SNIP2.02
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TL;DR
This research explores the robustness of simple linear regression and artificial neural networks with respect to varying sample size and variance of the error term by comparing their predictive abilities.
Abstract
This research explores the robustness of simple linear regression and artificial neural networks with respect to varying sample size and variance of the error term by comparing their predictive abilities. The comparison is made using the root mean square difference between the predicted output from each technique and the actual output.
Keywords
Computer Science
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