mirror of
https://github.com/webclinic017/drift.git
synced 2026-08-04 06:37:45 +00:00
Mark Aron Szulyovszky
a9b05dbd42
* fix(Reporting): use weighted average (with no_of_samples as weights) and only report level-1 OR level-2 model performance * chore(Config): updated sweep config * fix(Reporting): missing import * fix(Evaluation): get_first_valid_return_index can deal with zero valid indexes * fix(Training): increase threshold for skipping assets * fix(DataLoader): target asset should be always the first column
49 lines
1.3 KiB
YAML
49 lines
1.3 KiB
YAML
program: run_sweep.py
|
|
method: bayes
|
|
project: price-forecasting
|
|
name: Level-2 models
|
|
metric:
|
|
goal: maximize
|
|
name: sharpe
|
|
parameters:
|
|
path :
|
|
value: 'data/'
|
|
expanding_window:
|
|
values: [True, False]
|
|
distribution: categorical
|
|
sliding_window_size:
|
|
values: [180, 280, 380]
|
|
distribution: categorical
|
|
retrain_every:
|
|
values: [10, 20, 30]
|
|
distribution: categorical
|
|
scaler:
|
|
value: 'minmax'
|
|
include_original_data_in_ensemble:
|
|
values: [True, False]
|
|
distribution: categorical
|
|
method:
|
|
value: 'classification'
|
|
no_of_classes:
|
|
values: ['two', 'three-balanced', 'three-imbalanced']
|
|
distribution: categorical
|
|
forecasting_horizon:
|
|
value: 1
|
|
load_other_assets:
|
|
values: [True, False]
|
|
distribution: categorical
|
|
log_returns:
|
|
value: True
|
|
index_column:
|
|
value: 'int'
|
|
level_1_models:
|
|
value: ["LR", "LDA", "KNN", "CART", "NB", "AB", "RF", "StaticMom"]
|
|
level_2_models:
|
|
values: [["LR"], ["LDA"], ["KNN"], ["CART"], ["NB"], ["AB"], ["RF"], ["Ensemble_Average"]]
|
|
distribution: categorical
|
|
own_features:
|
|
values: [['single_mom', 'date_days'], [], ['level_1', 'date_days'], ['date_days', 'level_2']]
|
|
distribution: categorical
|
|
other_features:
|
|
values: [[], ['level_1']]
|
|
distribution: categorical |