Files
drift/sweep_ensemble.yaml
T
Mark Aron SzulyovszkyandGitHub 18768c3925 fix(FeatureExtractor): use a rolling z-score instead of StandardScaler with unavoidable lookahead bias (#146)
* fix(FeatureExtractor): use a rolling z-score instead of StandardScaler with unavoidable lookahead bias

* chore(Archive): removed archived models

* fix(FeatureExtractors): syntax

* fix(FeatureExtractors): mistake with expanding window
2022-01-10 14:24:51 +01:00

56 lines
1.4 KiB
YAML

program: run_sweep.py
method: grid
project: price-forecasting
name: Meta labelling
metric:
goal: maximize
name: sharpe
parameters:
primary_models_meta_labeling:
value: True
assets:
value: ['daily_crypto']
other_assets:
value: ['daily_etf']
exogenous_data:
value: ['daily_glassnode']
expanding_window_primary:
value: True
expanding_window_meta_labeling:
value: True
sliding_window_size_primary:
value: 380
sliding_window_size_meta_labeling:
value: 380
n_features_to_select:
value: 50
dimensionality_reduction:
value: True
retrain_every:
value: 20
scaler:
value: 'minmax'
method:
value: 'classification'
no_of_classes:
value: 'two'
forecasting_horizon:
value: 1
load_non_target_asset:
value: True
log_returns:
value: True
index_column:
value: 'int'
primary_models:
value: ["LDA", "KNN", "SVC", "CART", "NB", "AB", "RF", "XGB_two_class", "LGBM", "StaticMom"]
meta_labeling_models:
values: [["LDA"], ["XGB_two_class"], ["LR_two_class"], ["LGBM"], ["LGBM", "LR_two_class"], ["XGB_two_class", "LDA"], ["XGB_two_class", "LR_two_class"]]
distribution: categorical
own_features:
value: ['date_days', 'level_2', 'lags_up_to_5']
other_features:
value: ['level_2', 'lags_up_to_5']
exogenous_features:
value: ['z_score']