Contents
How is the error function calculated in neuralnet?
If the error function is equal to the negative log-likelihood function, the information criteria AIC and BIC will be calculated. Furthermore the usage of confidence.interval is meaningfull. neuralnet returns an object of class nn. An object of class nn is a list containing at most the following components:
How to fitting a neural network in R?
You need to first write the formula and then pass it as an argument in the fitting function. The neuralnet package provides a nice tool to plot the model: The black lines show the connections between each layer and the weights on each connection while the blue lines show the bias term added in each step.
What should MSE be for fitting neural network?
Since we are dealing with a regression problem, we are going to use the mean squared error (MSE) as a measure of how much our predictions are far away from the real data. Before fitting a neural network, some preparation need to be done.
Which is the best algorithm for training neural networks?
Riedmiller M. and Braun H. (1993) A direct adaptive method for faster backpropagation learning: The RPROP algorithm. Proceedings of the IEEE International Conference on Neural Networks (ICNN), pages 586-591. San Francisco. Anastasiadis A. et. al. (2005) New globally convergent training scheme based on the resilient propagation algorithm.
Which is the best function to train neural networks?
Train neural networks using backpropagation, resilient backpropagation (RPROP) with (Riedmiller, 1994) or without weight backtracking (Riedmiller and Braun, 1993) or the modified globally convergent version (GRPROP) by Anastasiadis et al. (2005). The function allows flexible settings through custom-choice of error and activation function.
What happens if act.fct is not applied to neurons?
If act.fct should not be applied to the output neurons set linear output to TRUE, otherwise to FALSE. a vector or a matrix specifying the weights, that are excluded from the calculation.