Lines Matching refs:n_bins

21 def test_histogram_split(n_bins):
29         rng.randint(0, n_bins - 1, size=(int(1e4), 1)), dtype=X_BINNED_DTYPE  argument
38     for true_bin in range(1, n_bins - 2):
47                 n_bins,
54                 [n_bins - 1] * X_binned.shape[1], dtype=np.uint32
61             missing_values_bin_idx = n_bins - 1
108     n_bins = 10
117         0, n_bins, size=(n_samples, n_features), dtype=X_BINNED_DTYPE
131         X_binned, n_bins, all_gradients, all_hessians, constant_hessian, n_threads
133     n_bins_non_missing = np.array([n_bins - 1] * X_binned.shape[1], dtype=np.uint32)
139     missing_values_bin_idx = n_bins - 1
245     n_bins = 5
274         X_binned, n_bins, all_gradients, all_hessians, hessians_are_constant, n_threads
276     n_bins_non_missing = np.array([n_bins] * X_binned.shape[1], dtype=np.uint32)
282     missing_values_bin_idx = n_bins - 1
336     n_bins = 255
339         rng.randint(0, n_bins, size=(n_samples, 1)), dtype=X_BINNED_DTYPE
350         X_binned, n_bins, all_gradients, all_hessians, hessians_are_constant, n_threads
352     n_bins_non_missing = np.array([n_bins - 1] * X_binned.shape[1], dtype=np.uint32)
358     missing_values_bin_idx = n_bins - 1
501     n_bins = max(X_binned) + 1
519         X_binned, n_bins, all_gradients, all_hessians, hessians_are_constant, n_threads
527     missing_values_bin_idx = n_bins - 1
604     n_bins = max(X_binned) + 1
623         X_binned, n_bins, all_gradients, all_hessians, hessians_are_constant, n_threads
631     missing_values_bin_idx = n_bins - 1
790     n_bins = max(X_binned) + 1
809         X_binned, n_bins, all_gradients, all_hessians, hessians_are_constant, n_threads