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@article{ART002683371},
author={baikjaewook},
title={Neural network analysis using neuralnet in R},
journal={Industry Promotion Research},
issn={2466-1139},
year={2021},
volume={6},
number={1},
pages={1-7},
doi={10.21186/IPR.2021.6.1.001}

TY - JOUR
AU - baikjaewook
TI - Neural network analysis using neuralnet in R
JO - Industry Promotion Research
PY - 2021
VL - 6
IS - 1
PB - Industrial Promotion Institute
SP - 1
EP - 7
SN - 2466-1139
AB - We investigated multi-layer perceptrons and supervised learning algorithms, and also examined how to model functional relationships between covariates and response variables using a package called neuralnet. The algorithm applied in this paper is characterized by continuous adjustment of the weights, which are parameters to minimize the error function based on the comparison between the actual and predicted values of the response variable. In the neuralnet package, the activation and error functions can be appropriately selected according to the given situation, and the remaining parameters can be set as default values. As a result of using the neuralnet package for the infertility data, we found that age has little influence on infertility among the four independent variables. In addition, the weight of the neural network takes various values from -751.6 to 7.25, and the intercepts of the first hidden layer are -92.6 and 7.25, and the weights for the covariates age, parity, induced, and spontaneous to the first hidden neuron are identified as 3.17, -5.20, -36.82, and –751.6.
KW - Multi-layer perceptron;Supervised learning;Back propagation;Neuralnet
DO - 10.21186/IPR.2021.6.1.001
ER -

baikjaewook. (2021). Neural network analysis using neuralnet in R. Industry Promotion Research, 6(1), 1-7.

baikjaewook. 2021, "Neural network analysis using neuralnet in R", Industry Promotion Research, vol.6, no.1 pp.1-7. Available from: doi:10.21186/IPR.2021.6.1.001

baikjaewook "Neural network analysis using neuralnet in R" Industry Promotion Research 6.1 pp.1-7 (2021) : 1.

baikjaewook. Neural network analysis using neuralnet in R. 2021; 6(1), 1-7. Available from: doi:10.21186/IPR.2021.6.1.001

baikjaewook. "Neural network analysis using neuralnet in R" Industry Promotion Research 6, no.1 (2021) : 1-7.doi: 10.21186/IPR.2021.6.1.001

baikjaewook. Neural network analysis using neuralnet in R. Industry Promotion Research, 6(1), 1-7. doi: 10.21186/IPR.2021.6.1.001

baikjaewook. Neural network analysis using neuralnet in R. Industry Promotion Research. 2021; 6(1) 1-7. doi: 10.21186/IPR.2021.6.1.001

baikjaewook. Neural network analysis using neuralnet in R. 2021; 6(1), 1-7. Available from: doi:10.21186/IPR.2021.6.1.001

baikjaewook. "Neural network analysis using neuralnet in R" Industry Promotion Research 6, no.1 (2021) : 1-7.doi: 10.21186/IPR.2021.6.1.001