Forward-propagate given data through the deep neural network.
# S3 method for DArch
predict(object, ..., newdata = NULL, type = "raw",
inputLayer = 1, outputLayer = 0)Further parameters, if newdata is NULL, the first
unnamed parameter will be used for newdata instead.
New data to predict, NULL to return latest network
output
Output type, one of: raw, bin, class, or
character. raw returns the layer output, bin returns
1 for every layer output >0.5, 0 otherwise, and
class returns 1 for the output unit with the highest
activation, otherwise 0. Additionally, when using class,
class labels are returned when available. character is the same as
class, except using character vectors instead of factors.
Layer number (> 0). The data given in
newdata will be fed into this layer.
Note that absolute numbers count from the input layer, i.e. for
a network with three layers, 1 would indicate the input layer.
Layer number (if > 0) or offset (if <= 0)
relative to the last layer. The output of the given layer is returned.
Note that absolute numbers count from the input layer, i.e. for
a network with three layers, 1 would indicate the input layer.
Vector or matrix of networks outputs, output type depending on the
type parameter.
Other darch interface functions: darchBench,
darchTest, darch,
plot.DArch, print.DArch
# NOT RUN {
data(iris)
model <- darch(Species ~ ., iris, retainData = T)
predict(model)
# }
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