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An Application of Discriminant Analysis and Artificial Neural Networks to Classification Problems
Yugoslav journal of operations research, Tome 11 (2001) no. 1, p. 113
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In this paper we present three algorithms to classify the elements of a population into two groups. The first algorithm is the classical multivariate statistical technique - discriminant analysis using Bayesian decision theory for the classification problem. The other two algorithms are two types of artificial neural networks: a feedforward three-layer network with a back-propagation learning algorithm and the probabilistic neural network. After discussing some theoretical attributes of these models, emphasis is placed on empirical results.
Classification : 68T05 62C10
Keywords: Classification, Fisher discriminant function, Bayesian decision theory, back-propagation algorithm, probabilistic neural network 
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     author = {Jasna Soldi\'c-Aleksi\'c},
     title = {An {Application} of {Discriminant} {Analysis} and {Artificial} {Neural} {Networks} to {Classification} {Problems}},
     journal = {Yugoslav journal of operations research},
     pages = {113 },
     year = {2001},
     volume = {11},
     number = {1},
     zbl = {1035.68098},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/YJOR_2001_11_1_a8/}
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Jasna Soldić-Aleksić. An Application of Discriminant Analysis and Artificial Neural Networks to Classification Problems. Yugoslav journal of operations research, Tome 11 (2001) no. 1, p. 113 . http://geodesic.mathdoc.fr/item/YJOR_2001_11_1_a8/