mirror of https://github.com/webclinic017/drift.git synced 2026-07-27 18:57:55 +00:00

T

Mark Aron Szulyovszky d3d7184ea4 feat(Models): added StaticAverageModel for average ensembling & StaticNaiveModel (#64 )

* feat(Models): added StaticAverageModel for average ensembling

* feat(Models): made sure we only pipe in predictions to StaticAverageModel, added StaticNaiveModel as potential baseline

* chore(Models): removed unnecessary commented out code

2021-12-21 15:57:08 +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

.vscode

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

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

archive

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

data

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

models

feat(Models): added StaticAverageModel for average ensembling & StaticNaiveModel (#64 )

2021-12-21 15:57:08 +01:00

tests

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

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

training

feat(Models): added StaticAverageModel for average ensembling & StaticNaiveModel (#64 )

2021-12-21 15:57:08 +01:00

utils

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

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

.gitignore

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

2021-12-20 14:01:14 +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 Weights and Biases configuration to the repo. (#48 )

2021-12-20 14:01:14 +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

feat(Models): added StaticAverageModel for average ensembling & StaticNaiveModel (#64 )

2021-12-21 15:57:08 +01:00

sweep.yaml

refactor(Core): small refactor in the pipeline to streamline classification/regression model handling (#60 )

2021-12-21 09:23:06 +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!:)