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feat(FeatureExtraction): added fractionally differentiated returns to remove lagged returns (#95)

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* feat(FeatureExtraction): added fractionally differentiated returns to remove lagged returns

* fix(Sweep): config

* fix(Sweep): name

* fix(Sweep): grid

* feat(Config): separated sliding_window_size_level1 & sliding_window_size_level2

* feat(Dependencies): added ray, now using it to parallel process feature extraction

* fix(Dependencies): added pip explicitly

* fix(Dependencies): removed ray from root

* fix(Models): average model was probably not taking the right timestamp to average

* feat(Config): separated expanding_window_level1 & expanding_window_level2

* fix(Config): set n_features_to_select to the optimal 30
This commit is contained in:
Mark Aron Szulyovszky
2021-12-28 22:50:09 +01:00
committed by GitHub
parent cc70d3f907
commit f762ceed2a
13 changed files with 626 additions and 417 deletions
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config.py
+13 -7
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@@ -7,10 +7,13 @@ from models.model_map import model_names_classification, model_names_regression
def get_default_level_1_config() -> tuple[dict, dict, dict]:
training_config = dict(
dimensionality_reduction = False,
dimensionality_reduction = True,
feature_selection = True,
expanding_window = False,
sliding_window_size = 380,
n_features_to_select = 30,
expanding_window_level1 = False,
expanding_window_level2 = False,
sliding_window_size_level1 = 380,
sliding_window_size_level2 = 1,
retrain_every = 20,
scaler = 'minmax', # 'normalize' 'minmax' 'standardize' 'none'
include_original_data_in_ensemble = False,
@@ -46,8 +49,11 @@ def get_default_level_2_config() -> tuple[dict, dict, dict]:
training_config = dict(
dimensionality_reduction = True,
feature_selection = True,
expanding_window = True,
sliding_window_size = 380,
n_features_to_select = 30,
expanding_window_level1 = True,
expanding_window_level2 = False,
sliding_window_size_level1 = 380,
sliding_window_size_level2 = 1,
retrain_every = 20,
scaler = 'minmax', # 'normalize' 'minmax' 'standardize' 'none'
include_original_data_in_ensemble = False,
@@ -59,8 +65,8 @@ def get_default_level_2_config() -> tuple[dict, dict, dict]:
load_other_assets= True,
log_returns= True,
forecasting_horizon = 1,
own_features = ['level_2', 'date_days', 'lags_up_to_5'],
other_features = ['level_2', 'lags_up_to_5'],
own_features = ['level_2', 'date_days', 'fracdiff'],
other_features = ['level_2', 'fracdiff'],
index_column= 'int',
method= 'classification',
no_of_classes= 'three-balanced'