LinearLBFGS
- class lightautoml.ml_algo.linear_sklearn.LinearLBFGS(default_params=None, freeze_defaults=True, timer=None, optimization_search_space={})[source]
Bases:
TabularMLAlgo
LBFGS L2 regression based on torch.
default_params:
cs: List of regularization coefficients.
max_iter: Maximum iterations of L-BFGS.
tol: The tolerance for the stopping criteria.
early_stopping: Maximum rounds without improving.
freeze_defaults:
True
: params may be rewrited depending on dataset.False
: params may be changed only manually or with tuning.
timer:
Timer
instance orNone
.- fit_predict_single_fold(train, valid)[source]
Train on train dataset and predict on holdout dataset.
- Parameters:
train (
Union
[NumpyDataset
,CSRSparseDataset
,PandasDataset
]) – Train Dataset.valid (
Union
[NumpyDataset
,CSRSparseDataset
,PandasDataset
]) – Validation Dataset.
- Return type:
- Returns:
Target predictions for valid dataset.
- predict_single_fold(model, dataset)[source]
Implements prediction on single fold.
- Parameters:
model (
TorchBasedLinearEstimator
) – Model uses to predict.dataset (
Union
[NumpyDataset
,CSRSparseDataset
,PandasDataset
]) –NumpyDataset
used for prediction.
- Return type:
- Returns:
Predictions for input dataset.