Fit clustering — fit_clustering • bascule

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.

Value

Bascule object.