- SKLearnModel.prepare(gene, lineage, backward=False, time_range=None, data_key='X', time_key='latent_time', use_raw=False, threshold=None, weight_threshold=(0.01, 0.01), filter_cells=None, n_test_points=200)
Prepare the model to be ready for fitting.
bool) – Direction of the process.
Specify start and end times:
int) – Number of test points. If None, use the original points based on
- Return type
Nothing, just updates the following fields:
x- Filtered independent variables of shape (n_filtered_cells, 1) used for fitting.
y- Filtered dependent variables of shape (n_filtered_cells, 1) used for fitting.
w- Filtered weights of shape (n_filtered_cells,) used for fitting.
x_all- Unfiltered independent variables of shape (n_cells, 1).
y_all- Unfiltered dependent variables of shape (n_cells, 1).
w_all- Unfiltered weights of shape (n_cells,).
x_test- Independent variables of shape (n_samples, 1) used for prediction.
prepared- Whether the model is prepared for fitting.