Deep MTS models — DeepMTS • nnetsauce

See also https://techtonique.github.io/nnetsauce/

DeepMTS(
  obj,
  n_layers = 3L,
  n_hidden_features = 5L,
  activation_name = "relu",
  a = 0.01,
  nodes_sim = "sobol",
  bias = TRUE,
  dropout = 0,
  direct_link = TRUE,
  n_clusters = 2L,
  cluster_encode = TRUE,
  type_clust = "kmeans",
  lags = 1L,
  replications = NULL,
  kernel = NULL,
  agg = "mean",
  seed = 123L,
  backend = c("cpu", "gpu", "tpu"),
  verbose = 0,
  venv_path = "./venv",
  ...
)

Arguments

obj: a model object
n_layers: number of hidden layers
...: additional parameters to be passed to nnetsauce::CustomRegressor

Examples


set.seed(123)
X <- matrix(rnorm(300), 100, 3)

obj <- sklearn$linear_model$ElasticNet()
#> Error: object 'sklearn' not found
obj2 <- DeepMTS(obj)
#> Error in reticulate::use_virtualenv(venv_path, required = TRUE): Directory ./venv is not a Python virtualenv

obj2$fit(X)
#> Error: object 'obj2' not found
obj2$predict()
#> Error: object 'obj2' not found