fit_clustering: Fit clustering
In caravagnalab/basilica: bascule

fit_clustering

R Documentation

Fit clustering

Description

Fit clustering

Usage

fit_clustering(
  x,
  cluster,
  hyperparameters = NULL,
  lr = 0.005,
  optim_gamma = 0.1,
  n_steps = 3000,
  py = NULL,
  enumer = "parallel",
  nonparametric = TRUE,
  autoguide = TRUE,
  CUDA = TRUE,
  compile = FALSE,
  store_parameters = FALSE,
  store_fits = TRUE,
  seed_list = c(10)
)

Arguments

`x`	Bascule object with signatures deconvolution performed.
`cluster`	Maximum number of clusters.
`hyperparameters`	List of hyperparameters passed to the NMF and clustering models.
`lr`	Learning rate for SVI optimizer.
`optim_gamma`	Deprecated.
`n_steps`	Number of steps for the inference.
`py`	User-installed version of `pybascule` package
`enumer`	Enumeration used for clustering (either 'parallel' or 'sequential').
`nonparametric`	Deprecated. The model only works in nonparametric way.
`autoguide`	Logical. If 'TRUE', the clustering model will use the Pyro autoguide.
`CUDA`	Logical. If 'TRUE' and a GPU is available, the models will run on GPU.
`compile`	Deprecated.
`store_parameters`	Logical. If 'TRUE', parameters at every step of inference will be stored in the object.
`store_fits`	Logical. If 'TRUE', all tested fits, i.e., for every value of 'K', will be stored in the object.
`seed_list`	List of seeds used for every input configuration.