Description Usage Arguments Value Examples
Defines parameters for optimizer and training procedure.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | scAlignOptions(
steps = 15000,
steps.decoder = 10000,
batch.size = 150,
learning.rate = 1e-04,
log.every = 5000,
architecture = "large",
batch.norm.layer = FALSE,
dropout.layer = TRUE,
num.dim = 32,
perplexity = 30,
betas = 0,
norm = TRUE,
full.norm = FALSE,
early.stop = FALSE,
walker.loss = TRUE,
reconc.loss = FALSE,
walker.weight = 1,
classifier.weight = 1,
classifier.delay = NA,
gpu.device = "0",
seed = 1234
)
|
steps |
(default: 15000) Number of training iterations for neural networks. |
steps.decoder |
Number of training iterations for neural networks. |
batch.size |
(default: 150) Number of input samples per training batch. |
learning.rate |
(default: 1e-4) Initial learning rate for ADAM. |
log.every |
(default: 5000) Number of steps before saving results. |
architecture |
(default: "small") Network function name for scAlign. |
batch.norm.layer |
(default: FALSE) Include batch normalization in the network structure. |
dropout.layer |
(default: TRUE) Include dropout in the network. |
num.dim |
(default: 32) Number of dimensions for joint embedding space. |
perplexity |
(default: 30) Determines the neighborhood size for each sample. |
betas |
(default: 0) Sets the bandwidth of the gaussians to be the same if > 0. Otherwise per cell beta is computed. |
norm |
(default: TRUE) Normalize the data mini batches while training scAlign (repeated). |
full.norm |
(default: FALSE) Normalize the data matrix prior to scAlign (done once). |
early.stop |
(default: TRUE) Early stopping during network training. |
walker.loss |
(default: TRUE) Add walker loss to model. |
reconc.loss |
(default: FALSE) Add reconstruction loss to model during alignment. |
walker.weight |
(default: 1.0) Weight on walker loss component |
classifier.weight |
(default: 1.0) Weight on classifier loss component |
classifier.delay |
(default: NULL) Delay classifier component of loss function until specific training step. Defaults to (2/3)*steps. |
gpu.device |
(default: '0') Which gpu to use. |
seed |
(default: 1245) Sets graph level random seed in tensorflow. |
Options data.frame
1 2 3 4 | options=scAlignOptions(steps=15000,
log.every=5000,
early.stop=FALSE,
architecture="large")
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.