Classification of escherichia coli bacteria by artificial neural networks

Through this paper, four different neural network structures which are: multilayer perceptron, radial basis function, general regression neural network and probabilistic neural network are applied to the escherichia coli bacteria benchmark and the most efficient neural network architecture for this data has been obtained. Better classification accuracy than the reference work using the ad hoc structured probability model was achieved by a probabilistic neural network.