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refactor(WalkForward): separate train / test functions to help with inference later (#158)

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* refactor(WalkForward): separate train / test functions (draft) to potentially help with inference later

* fix(Training): use the new separate train / test functions

* feat(Training): return and pass in scalers that are necessary for inference

* fix(Project): runtime errors

* fix(WalkForward): use the correct `train_from` value

* fix(Tests): for new walk_forward functions()

* refactor(WalkForward): rename `walk_forward_test()` to `walk_forward_inference()`
This commit is contained in:
Mark Aron Szulyovszky
2022-01-12 14:42:16 +01:00
committed by GitHub
parent 5db2a3b935
commit c611481eb6
7 changed files with 101 additions and 50 deletions
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utils/scaler.py
+3 -3
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@@ -1,8 +1,8 @@
from sklearn.preprocessing import MinMaxScaler, Normalizer, StandardScaler
from typing import Optional, Union
from typing import Union
from utils.types import ScalerTypes
def get_scaler(type: ScalerTypes) -> Optional[Union[MinMaxScaler, Normalizer, StandardScaler]]:
def get_scaler(type: ScalerTypes) -> Union[MinMaxScaler, Normalizer, StandardScaler]:
if type == 'normalize':
return Normalizer()
elif type == 'minmax':
@@ -10,4 +10,4 @@ def get_scaler(type: ScalerTypes) -> Optional[Union[MinMaxScaler, Normalizer, St
elif type == 'standardize':
return StandardScaler()
else:
return None
raise Exception("Scaler type not supported")