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In rnn package in R, the example shows how to train a RNN with numeric input variables.

The example code is:

library('rnn')

# create training numbers
set.seed(1)
X1 = sample(0:127, 7000, replace=TRUE)
X2 = sample(0:127, 7000, replace=TRUE)

# create training response numbers
Y <- X1 + X2

# convert to binary
X1 <- int2bin(X1, length=8)
X2 <- int2bin(X2, length=8)
Y  <- int2bin(Y,  length=8)

# create 3d array: dim 1: samples; dim 2: time; dim 3: variables
X <- array( c(X1,X2), dim=c(dim(X1),2) )

# train the model
model <- trainr(Y=Y,
                X=X,
                learningrate   =  0.1,
                hidden_dim     = 10,
                start_from_end = TRUE )

In the above example, X1 and X2 are numerical variables.

How can I train a RNN model in R if the input variables are factor?

Thanks a lot,

rawr
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Yang Mei Lian
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1 Answers1

0

have you tried coercing the factor to numeric:

Y <- as.numeric(Y)

For predicted values you would want to round them and then apply the levels again:

pred <- round(pred)

pred <- as.factor(pred, labels = c(...))
Bastiaan Quast
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