BayesianRVFLRegressor.Rd
Parameters' description can be found at https://techtonique.github.io/nnetsauce/
BayesianRVFLRegressor(
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",
s = 0.1,
sigma = 0.05,
seed = 123L,
backend = c("cpu", "gpu", "tpu")
)
set.seed(123)
n <- 50 ; p <- 3
X <- matrix(rnorm(n * p), n, p) # no intercept!
y <- rnorm(n)
(index_train <- base::sample.int(n = nrow(X),
size = floor(0.8*nrow(X)),
replace = FALSE))
#> [1] 47 23 3 9 39 30 31 45 50 36 34 22 28 29 33 19 12 21 17 44 40 48 25 18 15
#> [26] 46 37 35 27 32 6 10 8 49 16 41 13 4 20 14
X_train <- X[index_train, ]
y_train <- y[index_train]
X_test <- X[-index_train, ]
y_test <- y[-index_train]
obj <- BayesianRVFLRegressor(n_hidden_features = 5L)
print(obj$fit(X_train, y_train))
#> Error in py_call_impl(callable, call_args$unnamed, call_args$named): AttributeError: 'list' object has no attribute 'dtype'
#> Run `reticulate::py_last_error()` for details.
print(obj$score(X_test, y_test))
#> Error in py_call_impl(callable, call_args$unnamed, call_args$named): AttributeError: 'NoneType' object has no attribute 'ndim'
#> Run `reticulate::py_last_error()` for details.