nn.test | R Documentation |
Test new samples by Trainded NN,return error rate for classification
nn.test(nn, x, y, t = 0.5)
nn |
nerual network trained by function nn.train |
x |
new samples to predict |
y |
new samples' label |
t |
threshold for classification. If nn.predict value >= t then label 1,else label 0 |
error rate
Xiao Rong
Var1 <- c(rnorm(50, 1, 0.5), rnorm(50, -0.6, 0.2)) Var2 <- c(rnorm(50, -0.8, 0.2), rnorm(50, 2, 1)) x <- matrix(c(Var1, Var2), nrow = 100, ncol = 2) y <- c(rep(1, 50), rep(0, 50)) nn <- nn.train(x, y, hidden = c(5)) test_Var1 <- c(rnorm(50, 1, 0.5), rnorm(50, -0.6, 0.2)) test_Var2 <- c(rnorm(50, -0.8, 0.2), rnorm(50, 2, 1)) test_x <- matrix(c(test_Var1, test_Var2), nrow = 100, ncol = 2) err <- nn.test(nn, test_x, y)
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