nn.test {deepnet}

Test new samples by Trainded NN

Description

Test new samples by Trainded NN,return error rate for classification

Usage

nn.test(nn, x, y, t = 0.5)

Arguments

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

Value

error rate

Author(s)

Xiao Rong

Examples

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)