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https://github.com/webclinic017/drift.git
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Daniel Szemerey
fc4e59a7d2
* feat: Added ensemble models to sweep and configured naming convention. * fix: Default value was misconfigured. * feat(Sweep): separated level-1 and level-2 sweep configs, skip assets with too few samples to train on, simplified model mapping * fix(Sweep): syntax error * chore(Sweep): set sweep names accordingly * fix(Sweep): set sliding window * fix(Sweep): adjusted sweep config * fix(Sweep): removed invalid feature extractor preset Co-authored-by: Mark Aron Szulyovszky <mark.szulyovszky@gmail.com>
49 lines
1.4 KiB
YAML
49 lines
1.4 KiB
YAML
program: run_sweep.py
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method: bayes
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project: price-forecasting
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name: Level-2 models
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metric:
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goal: maximize
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name: sharpe
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parameters:
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path :
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value: 'data/'
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expanding_window:
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values: [True, False]
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distribution: categorical
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sliding_window_size:
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values: [180, 280, 380]
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distribution: categorical
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retrain_every:
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values: [10, 20, 30]
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distribution: categorical
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scaler:
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value: 'minmax'
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include_original_data_in_ensemble:
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values: [True, False]
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distribution: categorical
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method:
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value: 'classification'
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no_of_classes:
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values: ['two', 'three-balanced', 'three-imbalanced']
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distribution: categorical
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forecasting_horizon:
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value: 1
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load_other_assets:
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values: [True, False]
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distribution: categorical
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log_returns:
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value: True
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index_column:
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value: 'int'
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level_1_models:
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value: ["LR", "LDA", "KNN", "CART", "NB", "AB", "RF", "StaticMom"]
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level_2_models:
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values: [["LR"], ["LDA"], ["KNN"], ["CART"], ["NB"], ["AB"], ["RF"], ["Ensemble_Average"]]
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distribution: categorical
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own_features:
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values: [['single_mom', 'date_days'], [], ['level_1', 'date_days'], ['date_days', 'level_2']]
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distribution: categorical
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other_features:
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values: [[], ['level_1'], ['level_2']]
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distribution: categorical |