Description Usage Arguments References Examples
Learn Gradient Descent
1 | learn_gd(X, y, alpha, hiddenSize)
|
X |
input data |
y |
output data |
alpha |
fraction of gradient descent |
hiddenSize |
size of the hidden layer |
http://qua.st/handcoding-gradient-descent/ http://iamtrask.github.io/2015/07/27/python-network-part2/
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | # input dataset
X = matrix(c(0,0,1,
0,1,1,
1,0,1,
1,1,1), nrow=4, byrow=TRUE)
# output dataset
y = matrix(c(0,
1,
1,
0), nrow=4)
# set parameters
alpha = 0.1
hiddenSize = 32
# also try using:
# alphas = c(0.001,0.01,0.1,1,10,100,1000)
# for (alpha in alphas) {
# print(paste("Training With Alpha", alpha))
# learn_gd(X, y, alpha, hiddenSize) }
# run gradient descent function
learn_gd(X, y, alpha, hiddenSize)
|
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