gavindiaz/drift

mirror of https://github.com/webclinic017/drift.git synced 2026-08-02 21:57:46 +00:00

T

Mark Aron Szulyovszky 25b64f5a3d refactor(Reporting): only report the last model's results, moved wandb-related functions to reporting (#69 )

* refactor(Reporting): only report the last model's results, moved wandb-related functions to `reporting`

* fix(Reporting): use .mean() on axis 1 to retain the metrics, fixed get_model_name()

* fix(Config): sweep file syntax

* fix(Config): changed hyperparameter search method to "bayes"

* chore(Sweep): adjusted sweep config based on the results we saw (removed Momentum as well)

* fix(Sweep): only use classification method for now, we're not yet prepared for regression

2021-12-22 12:04:38 +01:00

.github/workflows

refactor(Project): move out load_data to utils, rename fetch_data to run_fetch_data, got classifiers to work (#38 )

2021-12-17 17:41:50 +01:00

feat(Pipeline): save results, train on all assets

2021-12-14 22:59:44 +01:00

refactor(Project): move out load_data to utils, rename fetch_data to run_fetch_data, got classifiers to work (#38 )

2021-12-17 17:41:50 +01:00

refactor(Project): move out load_data to utils, rename fetch_data to run_fetch_data, got classifiers to work (#38 )

2021-12-17 17:41:50 +01:00

feature_extractors

feat(Data): added feature extractors, and feature extractor presets, removed a bunch of custom arguments from load_data (#42 )

2021-12-19 12:14:59 +01:00

refactor(Reporting): only report the last model's results, moved wandb-related functions to reporting (#69 )

2021-12-22 12:04:38 +01:00

refactor(Reporting): only report the last model's results, moved wandb-related functions to reporting (#69 )

2021-12-22 12:04:38 +01:00

feat(Model): added own Model class, SkLearnModel wrapper and StaticMomentumModel (#61 )

2021-12-21 10:30:09 +01:00

refactor(Reporting): only report the last model's results, moved wandb-related functions to reporting (#69 )

2021-12-22 12:04:38 +01:00

refactor(Reporting): only report the last model's results, moved wandb-related functions to reporting (#69 )

2021-12-22 12:04:38 +01:00

.gitignore

feature: Added Weights and Biases configuration to the repo. (#48 )

2021-12-20 14:01:14 +01:00

config.py

refactor(Reporting): only report the last model's results, moved wandb-related functions to reporting (#69 )

2021-12-22 12:04:38 +01:00

conftest.py

feat(Tests): added basic unit tests for walk_forward_train_test() (#22 )

2021-12-15 17:54:03 +01:00

environment.yml

Feature: Added sweep functionality (#65 )

2021-12-21 17:28:36 +01:00

exploration.ipynb

feat(Models): added model that predicts 10 days ahead

2021-11-12 16:10:55 +01:00

README.md

feat(Core): ensemble models, correct forward returns calculation, scaling, only train from when asset returns are available, major bug fixed in walk_forward_train_test (#35 )

2021-12-17 14:32:17 +01:00

run_fetch_data.py

refactor(Project): move out load_data to utils, rename fetch_data to run_fetch_data, got classifiers to work (#38 )

2021-12-17 17:41:50 +01:00

run_pipeline.py

refactor(Reporting): only report the last model's results, moved wandb-related functions to reporting (#69 )

2021-12-22 12:04:38 +01:00

run_sweep.py

Feature: Added sweep functionality (#65 )

2021-12-21 17:28:36 +01:00

sweep.yaml

refactor(Reporting): only report the last model's results, moved wandb-related functions to reporting (#69 )

2021-12-22 12:04:38 +01:00

wandb_setup.py

feature: Added Weights and Biases configuration to the repo. (#48 )

2021-12-20 14:01:14 +01:00

README.md

Financial time series prediction models

Installation

Use the conda environment file attached!:)