(self, X=None, y=None, cat_features=None, text_features=None, embedding_features=None,
pairs=None, graph=None, sample_weight=None, group_id=None, group_weight=None, subgroup_id=None,
pairs_weight=None, baseline=None, use_best_model=None, eval_set=None, verbose=None,
logging_level=None, plot=None, plot_file=None, column_description=None, verbose_eval=None,
metric_period=None, silent=None, early_stopping_rounds=None, save_snapshot=None,
snapshot_file=None, snapshot_interval=None, init_model=None, callbacks=None)
| 2562 | ) |
| 2563 | |
| 2564 | def _prepare_train_params(self, X=None, y=None, cat_features=None, text_features=None, embedding_features=None, |
| 2565 | pairs=None, graph=None, sample_weight=None, group_id=None, group_weight=None, subgroup_id=None, |
| 2566 | pairs_weight=None, baseline=None, use_best_model=None, eval_set=None, verbose=None, |
| 2567 | logging_level=None, plot=None, plot_file=None, column_description=None, verbose_eval=None, |
| 2568 | metric_period=None, silent=None, early_stopping_rounds=None, save_snapshot=None, |
| 2569 | snapshot_file=None, snapshot_interval=None, init_model=None, callbacks=None): |
| 2570 | params = deepcopy(self._get_canonized_params()) |
| 2571 | |
| 2572 | if isinstance(X, FeaturesData): |
| 2573 | warnings.warn("FeaturesData is deprecated for using in fit function " |
| 2574 | "and soon will not be supported. If you want to use FeaturesData, " |
| 2575 | "please pass it to Pool initialization and use Pool in fit") |
| 2576 | |
| 2577 | cat_features = _process_feature_indices(cat_features, X, params, 'cat_features') |
| 2578 | text_features = _process_feature_indices(text_features, X, params, 'text_features') |
| 2579 | embedding_features = _process_feature_indices(embedding_features, X, params, 'embedding_features') |
| 2580 | |
| 2581 | train_pool = _build_train_pool(X, y, cat_features, text_features, embedding_features, pairs, graph, |
| 2582 | sample_weight, group_id, group_weight, subgroup_id, pairs_weight, |
| 2583 | baseline, column_description) |
| 2584 | if train_pool.is_empty_: |
| 2585 | raise CatBoostError("X is empty.") |
| 2586 | |
| 2587 | allow_clear_pool = not isinstance(X, Pool) |
| 2588 | |
| 2589 | params['loss_function'] = _get_loss_function_for_train( |
| 2590 | params, |
| 2591 | getattr(self, '_estimator_type', None), |
| 2592 | train_pool |
| 2593 | ) |
| 2594 | |
| 2595 | metric_period, verbose, logging_level = _process_verbose( |
| 2596 | metric_period, verbose, logging_level, verbose_eval, silent) |
| 2597 | |
| 2598 | if metric_period is not None: |
| 2599 | params['metric_period'] = metric_period |
| 2600 | if logging_level is not None: |
| 2601 | params['logging_level'] = logging_level |
| 2602 | if verbose is not None: |
| 2603 | params['verbose'] = verbose |
| 2604 | if use_best_model is not None: |
| 2605 | params['use_best_model'] = use_best_model |
| 2606 | |
| 2607 | if early_stopping_rounds is not None: |
| 2608 | params['od_type'] = 'Iter' |
| 2609 | params['od_wait'] = early_stopping_rounds |
| 2610 | if 'od_pval' in params: |
| 2611 | del params['od_pval'] |
| 2612 | |
| 2613 | if save_snapshot is not None: |
| 2614 | params['save_snapshot'] = save_snapshot |
| 2615 | |
| 2616 | if snapshot_file is not None: |
| 2617 | params['snapshot_file'] = snapshot_file |
| 2618 | |
| 2619 | if snapshot_interval is not None: |
| 2620 | params['snapshot_interval'] = snapshot_interval |
| 2621 |
no test coverage detected