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R: Mining Spatial, Text, Web, and Social Media Data by Richard Heimann, Nathan Danneman, Pradeepta Mishra, Bater Makhabel

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Neural network implementation in R

R programming for statistical computing provides three different libraries to perform the neural network model for various tasks. These three are nnet, neuralnet, and rsnns. In this chapter, we will use ArtPiece_1.csv and two libraries, nnet and neuralnet, to perform various tasks. The syntax for neural networks in those two libraries can be explained as follows.

The neuralnet library depends on two other libraries, grid and mass; while installing the neuralnet library, you have to make sure that these two dependency libraries are installed properly. In fitting a neural network model, the desired level of accuracy in a model defines the required number of hidden layers with the number of neurons in it; the number ...

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