refactor(weights): align _train with BaseRegressionModel.train

refactor(weights): align _train with BaseRegressionModel.train

Rename _train_default to _train to match the upstream method name (with
underscore prefix to mark it as the internal mirror, since the public
train() method routes between data split paths).

Mirror BaseRegressionModel.train line-for-line with _compose_train_weights
as the single intentional insertion between make_train_test_datasets and
the pipeline application:

- Drop ensure_datetime_series wrapper around unfiltered_df['date']:
  upstream calls .iloc[].strftime() directly.
- Drop **kwargs from self.fit(dd, dk) to match upstream signature.
- Use dk.data_dictionary['train_features'].columns for feature count log,
  matching upstream source of truth.
- Apply the same cosmetic alignment to the timeseries_split path for
  consistency between both train code paths.
- Add docstring documenting the mirror relationship and the single
  functional difference.