predict.rpudl {rpud} | R Documentation |
Predict the classification outcome of a collection of input vectors based on a trained RPUDL model.
## S3 method for class 'rpudl' predict( model, x, ..., log.level = 1 )
model |
a trained |
x |
An m by n matrix, where m is the size of each input vector, and n is the number of input vectors |
... |
further arguments to be passed to or from methods |
log.level |
level of the method output (0 = silent, 1 = basic output, 2 = detailed output) |
A vector whose length is the number of input vectors.
the 'i-th' entry in the vector is the prediction class
of the 'i-th' input vector.
The probability output of each input vector is stored in the
"decision.values"
.
Chi Yau
chi.yau@r-tutor.com
rpudl,
rpudlDataSource,
rpudlTestDataSample,
rpudlTrain
## Not run: # create data source ds <- rpudlDataSource( data.format="lmdb", data.dir="data/mnist", train.data="mnist-official-data_train_lmdb", test.data="mnist-official-data_test_lmdb", data.shape=c(28, 28) ) # create model model <- rpudl( "mnist_mpl_lenet.prototxt", data.source=ds ) # train model model <- rpudlTrain(model, batch=100, iter=1000) # extract some test samples num <- 12 obj <- rpudlTestDataSample(ds, c(1, num)) # predictions res <- predict(model, obj$x) # find num of errors sum((obj$y+1) == res) ## End(Not run)