feat(Transformations): added robust scaler (#223)

* feat(Transformations): added robust scaler

* fix(Config): set back default scaler to MinMax

config/presets.py

@@ -15,10 +15,10 @@ def get_default_config() -> RawConfig:
 
     return RawConfig(
         dimensionality_reduction_ratio=0.5,
-        n_features_to_select=30,
+        n_features_to_select=50,
         sliding_window_size=3800,
         retrain_every=1000,
-        scaler="minmax",  # 'normalize' 'minmax' 'standardize'
+        scaler="minmax",  # 'normalize' 'minmax' 'standardize' 'robust'
         assets=["fivemin_crypto"],
         target_asset="BTC_USD",
         other_assets=[],

config/types.py

@@ -3,7 +3,7 @@ from typing import Literal, Optional
 from labeling.types import EventFilter
 from models.base import Model
 from data_loader.types import DataCollection, DataSource
-from feature_extractors.types import FeatureExtractor, ScalerTypes
+from feature_extractors.types import FeatureExtractor
 from labeling.types import EventFilter, EventLabeller
 from sklearn.base import BaseEstimator
 from dataclasses import dataclass
@@ -15,7 +15,7 @@ class RawConfig(BaseModel):
     n_features_to_select: int
     sliding_window_size: int
     retrain_every: int
-    scaler: Literal["normalize", "minmax", "standardize"]
+    scaler: Literal["normalize", "minmax", "standardize", "robust"]
 
     assets: list[str]
     target_asset: str