2018
DOI: 10.18637/jss.v085.i11
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NeuralNetTools: Visualization and Analysis Tools for Neural Networks

Abstract: Supervised neural networks have been applied as a machine learning technique to identify and predict emergent patterns among multiple variables. A common criticism of these methods is the inability to characterize relationships among variables from a fitted model. Although several techniques have been proposed to "illuminate the black box", they have not been made available in an open-source programming environment. This article describes the NeuralNetTools package that can be used for the interpretation of su… Show more

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Cited by 228 publications
(160 citation statements)
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“…for two hidden layers, testing 40 total nodes would have tested 10, 20 and 30 nodes in layer 1 and 30, 20 and 10 nodes in layer 2, respectively. The relative variable importance was computed using the olden function in the R package NeuralNetTools [24].…”
Section: (E) Population Modelling and Deep Learningmentioning
confidence: 99%
“…for two hidden layers, testing 40 total nodes would have tested 10, 20 and 30 nodes in layer 1 and 30, 20 and 10 nodes in layer 2, respectively. The relative variable importance was computed using the olden function in the R package NeuralNetTools [24].…”
Section: (E) Population Modelling and Deep Learningmentioning
confidence: 99%
“…The classification accuracy has been measured separately for normal, noisy and a combined data set. Analysis was conducted in R [22] with signal [23] and neuralnet [24] libraries on Intel i7, 8 MB RAM workstation.…”
Section: Resultsmentioning
confidence: 99%
“…; Venables & Ripley ) used in this study is a relatively simple implementation using a feedforward network with a single hidden layer, and includes two main parameters that need to be adjusted to optimise performance: Size , which specifies the number of nodes in the hidden layer, and Decay , which is a regularisation parameter applied to weighting factors to minimise overfitting. Examples of NN structures applied to the obsidian data are shown in Supporting Information Figure (see also Beck ).…”
Section: Methodsmentioning
confidence: 99%