From 69821878726900cfd52517c38ddbe713c529c0be Mon Sep 17 00:00:00 2001 From: Mark Aron Szulyovszky Date: Sat, 8 Jan 2022 00:10:45 +0100 Subject: [PATCH] feat(Sweep): new config to test dynamic features selection, number of features, etc. (#127) --- ...p_meta.yaml => sweep_dynamic_features.yaml | 16 +++-- sweep_exo_data.yaml | 58 ------------------- 2 files changed, 10 insertions(+), 64 deletions(-) rename sweep_meta.yaml => sweep_dynamic_features.yaml (77%) delete mode 100644 sweep_exo_data.yaml diff --git a/sweep_meta.yaml b/sweep_dynamic_features.yaml similarity index 77% rename from sweep_meta.yaml rename to sweep_dynamic_features.yaml index b576150..5e990eb 100644 --- a/sweep_meta.yaml +++ b/sweep_dynamic_features.yaml @@ -6,9 +6,11 @@ metric: goal: maximize name: sharpe parameters: - meta_labeling_lvl_1: + dynamic_feature_selection: values: [True, False] - distribution: categorical + distribution: 'categorical' + meta_labeling_lvl_1: + value: True assets: value: ['daily_crypto'] other_assets: @@ -16,7 +18,8 @@ parameters: exogenous_data: value: ['daily_glassnode'] expanding_window_level1: - value: False + values: [False, True] + distribution: 'categorical' expanding_window_level2: value: True sliding_window_size_level1: @@ -24,7 +27,8 @@ parameters: sliding_window_size_level2: value: 380 n_features_to_select: - value: 30 + values: [30, 50, 70, 80] + distribution: 'categorical' dimensionality_reduction: value: True retrain_every: @@ -44,9 +48,9 @@ parameters: index_column: value: 'int' level_1_models: - value: ["LDA", "KNN", "SVC", "CART", "NB", "AB", "RF", "StaticMom"] + value: ["LDA", "KNN", "SVC", "CART", "NB", "AB", "RF", "XGB_two_class", "StaticMom"] level_2_model: - values: ["LDA", "KNN", "NB", "AB", "RF", "XGB_two_class"] + values: ["LDA", "XGB_two_class"] distribution: categorical own_features: value: ['date_days', 'level_2', 'lags_up_to_5'] diff --git a/sweep_exo_data.yaml b/sweep_exo_data.yaml deleted file mode 100644 index b99f49a..0000000 --- a/sweep_exo_data.yaml +++ /dev/null @@ -1,58 +0,0 @@ -program: run_sweep.py -method: grid -project: price-forecasting -name: Exogenous data / data transformation -metric: - goal: maximize - name: sharpe -parameters: - meta_labeling_lvl_1: - value: True - assets: - value: ['daily_crypto'] - other_assets: - value: ['daily_etf'] - exogenous_data: - values: [['daily_glassnode'], []] - distribution: categorical - expanding_window_level1: - value: True - expanding_window_level2: - value: False - sliding_window_size_level1: - value: 380 - sliding_window_size_level2: - value: 1 - n_features_to_select: - value: 30 - dimensionality_reduction: - value: True - retrain_every: - value: 20 - scaler: - value: 'minmax' - method: - value: 'classification' - no_of_classes: - value: 'three-balanced' - forecasting_horizon: - value: 1 - load_non_target_asset: - value: True - log_returns: - value: True - index_column: - value: 'int' - level_1_models: - value: ["LR", "LDA", "KNN", "CART", "NB", "AB", "RF", "StaticMom"] - level_2_model: - value: "Ensemble_Average" - own_features: - values: [['date_days', 'level_2', 'lags_up_to_5'], ['date_days', 'level_2', 'fracdiff']] - distribution: categorical - other_features: - values: [['level_2', 'lags_up_to_5'], ['level_2', 'fracdiff']] - distribution: categorical - exogenous_features: - values: [[], ['fracdiff'], ['standard_scaling']] - distribution: categorical