A Modified Kennard-Stone Algorithm for Optimal Division of Data for Developing Artificial Neural Network Models

A Modified Kennard-Stone Algorithm for Optimal Division of Data for Developing Artificial Neural Network Models

This paper proposes a method, namely MDKS (Kennard-Stone algorithm based on Mahalanobis distance), to divide the data into training and testing subsets for developing artificial neural network (ANN) models. This method is a modified version of the Kennard-Stone (KS) algorithm. With this method, bett...

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Bibliographic Details
Main Authors: Saptoro, Agus, Tade, Moses, Vuthaluru, Hari
Format: Journal Article
Published: The Berkeley Electronic Press 2012
Subjects:
data division
kennard-stone algorithm
ANN models
MDKS
Online Access:http://hdl.handle.net/20.500.11937/45101

Internet

http://hdl.handle.net/20.500.11937/45101

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