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Aug 25th, 2019
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  1. gesture.neural.model = read.csv("gesture.training.csv", header=TRUE, sep=" ", quote="\"")
  2. str(gesture.neural.model)
  3.  
  4. max.values = apply(gesture.neural.model, 2, max)
  5. min.values = apply(gesture.neural.model, 2, min)
  6.  
  7. gesture.neural.model.scaled = as.data.frame(scale(gesture.neural.model, center=min.values, scale=max.values - min.values))
  8.  
  9. require(neuralnet)
  10. library(neuralnet)
  11.  
  12. NN = neuralnet(okay ~ PC1 + PC2 + PC3 + PC4 + PC5 + PC6 + PC7 + PC8 + PC9 + PC10, gesture.neural.model.scaled, threshold=0.05, learningrate=0.001, hidden=c(1,3), linear.output=TRUE, startweights=rep(0, 14))
  13. plot(NN)
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