Determining the Best Model With Deep Neural Networks: Keras Application on Mushroom Data

Abstract

This study was conducted to reveal the best classifying model with deep neural networks. For this purpose, 20 different candidate models of optimization method (Sgd, Adagrad, Rmsprop, Adam and Nadam), activation function (Tanh and ReLU) and combinations of neurons were studied. By comparing the performance of these candidate models, the best model for classification was determined. The present results indicated that the performance of the models varied according to the parameters, the most successful model has 64 neurons in the hidden layer, the activation function was ReLU and the Rmsprop was used as the optimization method (92% accuracy). In addition, it was determined that the model with the lowest success rate was the model with 32 neurons, ReLU activation function and Sgd optimization method (70% accuracy). Also considering all results; Rmsprop, Adam and Nadam optimization methods were found to be more successful than the other two methods and ReLU activation function produced more successful results than Tanh. © 2019, Centenary University. All rights reserved.