fix(Config): adjusted parameters to 5 minute timeframe

config/preprocess.py

@@ -96,7 +96,10 @@ def __preprocess_event_labeller_config(config_dict: dict) -> dict:
 def __preprocess_transformations_config(config_dict: dict) -> dict:
     transformations = [
         get_scaler(config_dict["scaler"]),
-        get_pca(config_dict["dimensionality_reduction_ratio"], config_dict["sliding_window_size"]),
+        get_pca(
+            config_dict["dimensionality_reduction_ratio"],
+            config_dict["sliding_window_size"],
+        ),
         get_rfe(config_dict["n_features_to_select"]),
     ]
     transformations = [x for x in transformations if x is not None]

config/presets.py

@@ -1,42 +1,7 @@
 from .types import RawConfig, Config
 
 
-def get_default_ensemble_config() -> RawConfig:
-
-    classification_models = [
-        "LogisticRegression_two_class",
-        "LDA",
-        "NB",
-        "RFC",
-        "XGB_two_class",
-        "LGBM",
-        "StaticMom",
-    ]
-    meta_models = ["LogisticRegression_two_class", "LGBM"]
-
-    return RawConfig(
-        dimensionality_reduction_ratio=0.5,
-        n_features_to_select=30,
-        sliding_window_size=380,
-        retrain_every=10,
-        scaler="minmax",  # 'normalize' 'minmax' 'standardize'
-        assets=["daily_crypto"],
-        target_asset="BTC_USD",
-        other_assets=["daily_etf"],
-        exogenous_data=["daily_glassnode"],
-        load_non_target_asset=True,
-        own_features=["level_2", "date_days", "lags_up_to_5"],
-        other_features=["level_2", "lags_up_to_5"],
-        exogenous_features=["z_score"],
-        directional_models=classification_models,
-        meta_models=meta_models,
-        event_filter="cusum_vol",
-        labeling="two_class",
-        forecasting_horizon=100,
-    )
-
-
-def get_lightweight_ensemble_config() -> RawConfig:
+def get_default_config() -> RawConfig:
 
     classification_models = [
         "LogisticRegression_two_class",
@@ -58,9 +23,9 @@ def get_lightweight_ensemble_config() -> RawConfig:
         target_asset="BTC_USD",
         other_assets=[],
         exogenous_data=[],
-        load_non_target_asset=False,
-        own_features=["level_1"],
-        other_features=[],
+        load_non_target_asset=True,
+        own_features=["level_2"],
+        other_features=["z_score"],
         exogenous_features=[],
         directional_models=classification_models,
         meta_models=meta_models,