Description Usage Arguments Value Author(s) See Also
Functions and methods for training generative neural networks.
1 2 3 4 5 6 7 8 9 10 | ## S3 method for class 'gnn_GNN'
fitGNN(x, data, batch.size = nrow(data), n.epoch = 100,
prior = NULL, max.n.prior = 5000, verbose = 2, ...)
## S3 method for class 'gnn_GNN'
fitGNNonce(x, data, batch.size = nrow(data), n.epoch = 100,
prior = NULL, verbose = 2, file = NULL, name = NULL, ...)
## S3 method for class 'gnn_GNN'
is.trained(x)
## S3 method for class 'list'
is.trained(x)
|
x |
|
data |
(n, d)-matrix containing the n d-dimensional observations of the training data. |
batch.size |
number of samples used per stochastic gradient step. |
n.epoch |
number of epochs (one epoch equals one pass through the complete training dataset while updating the GNN's parameters through stochastic gradient steps). |
prior |
(n, d)-matrix of prior samples; see also
|
max.n.prior |
maximum number of prior samples stored in |
verbose |
|
file |
|
name |
|
... |
additional arguments passed to the underlying
|
the trained x
.
object of class as x
with the trained GNN.
logical
indicating whether x
is trained.
logical
of length
length(x)
indicating, for each component, whether
it is trained.
Marius Hofert
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