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drift/environment.yml
T
Mark Aron Szulyovszky 1cd0119589 feat(DataLoader): caching MVP, added ability to use standard scaling for exogenous data, scaling is now also done before feature selection (#105)
* fix(FeatureExtractor): apply log to transform some series to normality

* feat(DataLoader): add ability of not returning returns when they're not needed (exogenous data), applied log to certain features

* feat(FeatureExtractors): added standard scaling for exogenous data

* feat(FeatureSelection): scale data with the passed in scaler before doing feature-selection

* fix(Config): sweep config

* feat(Models): output probability, store it

* feat(Core): added caching to select_features() and load_data()

* fix(Dependencies): added diskcache

* fix(Training): error when creating results DF

* feat(Models): added xgboost, fixed tests

* refactor(Cache): moved hashing to a separate function, created wrapper functions to separate business logic and caching

* fix(Tests): new syntax

* fix(Model): XGboost can't handle -1 class, so we'll use the deprecated label_encoder fornow

* fix(Model): XGBoost config

* feat(Cache): add run_clear_cache script

* fix(Pipeline) accidentally re-instatiating all_predictions for each asset
2022-01-04 11:44:35 +01:00

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YAML

name: quant
channels:
- johnsnowlabs
- conda-forge
- defaults
dependencies:
- python=3.9
- seaborn
- scikit-learn-intelex=2021.4.0
- ipython
- ipykernel
- scipy
- scikit-learn
- numba
- pytorch
- matplotlib
- numpy
- quantstats
- pytorch-lightning
- pytest
- wandb
- python-dotenv
- tscv
- tqdm
- pip
- pandas-ta
- xgboost
- pip:
- fracdiff
- ray
- diskcache
prefix: /usr/local/anaconda3/envs/quant