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Function elmtrain [elmNN v1.0]
keywords
neural
title
Training of a SLFN (Single Hidden-layer Feedforward Neural Network)
description
Training of a generic SLFN using ELM algorithm. First it generates input weights and hidden layer bias ( both randomly choosen ), then calculates the output from the hidden layer ( given a particular activation function as a parameter ) and at the end calculates output weights of the neural network. It returns an ELM model ( an object of class elmNN ) representing the trained neural network.
Function predict.elmNN [elmNN v1.0]
keywords
neural
title
Calculate the output of the ELM-trained neural network
description
Calculate the output predictions from a neural network trained using elmtrain. It is possible to calculate output predictions from a new data set or returns the output predictions from the previous training data set ( fitted data ).
Function confidence.interval [neuralnet v1.33]
keywords
neural
title
Calculates confidence intervals of the weights
description
confidence.interval, a method for objects of class nn, typically produced by neuralnet. Calculates confidence intervals of the weights (White, 1989) and the network information criteria NIC (Murata et al. 1994). All confidence intervals are calculated under the assumption of a local identification of the given neural network. If this assumption is violated, the results will not be reasonable. Please make also sure that the chosen error function equals the negative log-likelihood function, otherwise the results are not meaningfull, too.
Function prediction [neuralnet v1.33]
keywords
neural
title
Summarizes the output of the neural network, the data and the fitted values of glm objects (if available)
description
prediction, a method for objects of class nn, typically produced by neuralnet. In a first step, the dataframe will be amended by a mean response, the mean of all responses corresponding to the same covariate-vector. The calculated data.error is the error function between the original response and the new mean response. In a second step, all duplicate rows will be erased to get a quick overview of the data. To obtain an overview of the results of the neural network and the glm objects, the covariate matrix will be bound to the output of the neural network and the fitted values of the glm object(if available) and will be reduced by all duplicate rows.
Function neuralnet [neuralnet v1.33]
keywords
neural
title
Training of neural networks
description
neuralnet is used to 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. Furthermore the calculation of generalized weights (Intrator O. and Intrator N., 1993) is implemented.
Function plot.nn [neuralnet v1.33]
keywords
neural
title
Plot method for neural networks
description
plot.nn, a method for the plot generic. It is designed for an inspection of the weights for objects of class nn, typically produced by neuralnet.
Function neuralnet-package [neuralnet v1.33]
keywords
neural
title
Training of Neural Networks
description
Training of neural networks using the backpropagation, resilient backpropagation with (Riedmiller, 1994) or without weight backtracking (Riedmiller, 1993) or the modified globally convergent version by Anastasiadis et al. (2005). The package allows flexible settings through custom-choice of error and activation function. Furthermore, the calculation of generalized weights (Intrator O & Intrator N, 1993) is implemented.
Function compute [neuralnet v1.33]
keywords
neural
title
Computation of a given neural network for given covariate vectors
description
compute, a method for objects of class nn, typically produced by neuralnet. Computes the outputs of all neurons for specific arbitrary covariate vectors given a trained neural network. Please make sure that the order of the covariates is the same in the new matrix or dataframe as in the original neural network.
Function gwplot [neuralnet v1.33]
keywords
neural
title
Plot method for generalized weights
description
gwplot, a method for objects of class nn, typically produced by neuralnet. Plots the generalized weights (Intrator and Intrator, 1993) for one specific covariate and one response variable.
Function pcaNNet [caret v6.0-73]
keywords
neural
title
Neural Networks with a Principal Component Step
description
Run PCA on a dataset, then use it in a neural network model