Commit Graph

31 Commits

Author SHA1 Message Date
lolong
9c051958a6
Feat/freqai (#7105)
Vectorize weight setting, log training dates

Co-authored-by: robcaulk <rob.caulk@gmail.com>
2022-07-19 17:49:18 +02:00
lolong
ed0f8b1189
Improve FreqAI documentation (#7072)
Improve doc + some other small fixes

Co-authored-by: robcaulk <rob.caulk@gmail.com>
2022-07-18 11:57:52 +02:00
robcaulk
4141d165ff add BaseTensorFlowModel class 2022-07-12 19:10:09 +02:00
robcaulk
ef409dd345 Add ground work for TensorFlow models, add protections from common mistakes 2022-07-12 18:09:17 +02:00
Robert Caulk
fea63fba12 Fix saving/loading historic predictions 2022-07-12 10:12:50 +02:00
Robert Caulk
8ce6b18318 start collecting indefinite history of predictions. Allow user to generate statistics on these predictions. Direct FreqAI to save these to disk and reload them if available. 2022-07-11 22:01:48 +02:00
Matthias
3fc92b1b21 Create BaseRegression model - designed to reduce code duplication across currently available models. 2022-07-11 11:33:59 +02:00
Robert Caulk
607455919e Change config parameter names to improve clarity and consistency throughout the code (!!breaking change, please check discord support channel for migration instructions or review templates/FreqaiExampleStrategy.py config_examples/config_freqai_futures.example.json file changes!!) 2022-07-10 12:35:44 +02:00
Matthias
819cc9c0e4 Fully align LightGBM with Catboost 2022-07-10 11:06:18 +02:00
Matthias
58b18770e3 Fix LightGBM missing argument in predict method 2022-07-10 11:05:35 +02:00
Matthias
2e1061af64 Fix faulty LightGBM model 2022-07-09 08:21:42 +00:00
robcaulk
8ac8d53c32 All LGBMRegressor model parameters are now set in config 2022-07-03 16:30:01 +02:00
robcaulk
ffb39a5029 black formatting on freqai files 2022-07-03 10:59:38 +02:00
robcaulk
106131ff0f Rehaul organization of return values 2022-07-02 18:09:38 +02:00
robcaulk
051b99791d reduce unnecessary verbosity, fix error on first training sweep, add LightGBMPredictionModel 2022-06-26 19:04:23 +02:00
robcaulk
f631ae911b add model expiration feature, fix bug in DI return values 2022-06-17 14:55:40 +02:00
robcaulk
c5de0c49e4 first functional scanning commit 2022-06-16 00:24:18 +02:00
Matthias
c981ad4608 Fix missing space 2022-06-12 08:31:02 +02:00
robcaulk
15d049cffe detect if upper tf candles are new or not, append if so. Correct the epoch for candle update check 2022-06-07 19:49:20 +02:00
robcaulk
f2762e3b4b fix bug in return_values() 2022-06-03 16:58:51 +02:00
robcaulk
16b4a5b71f rehaul of backend data management - increasing performance by holding history in memory, reducing load on the ratelimit by only pinging exchange once per candle. Improve code readability. 2022-06-03 15:19:46 +02:00
robcaulk
c5a16e91fb throw user error if user tries to load models but feeds the wrong features (while using PCA) 2022-05-28 11:11:41 +02:00
robcaulk
6193205012 fix bug for target_mean/std array merging in backtesting 2022-05-26 21:07:50 +02:00
robcaulk
255d35976e add priority metadata to pairs to avoid a sync of train time + train period 2022-05-24 12:58:53 +02:00
robcaulk
059c285425 paying closer attention to managing live retraining on separate thread without affecting prediction of other coins on master thread 2022-05-24 12:01:01 +02:00
robcaulk
b0d2d13eb1 improve data persistence/mapping for live/dry. This accommodates quick reloads after crash and handles multi-pair cleanly 2022-05-23 21:05:05 +02:00
robcaulk
e1c068ca66 add config asserts, use .get method with default values for optional functionality, move data_cleaning_* to freqai_interface (away from user custom pred model) since it is controlled by config params. 2022-05-23 12:07:09 +02:00
robcaulk
af0cc21af9 Enable hourly/minute retraining in live/dry. Suppress catboost folder output. Update config + constants + docs to reflect updates. 2022-05-23 00:06:26 +02:00
robcaulk
42d95af829 Aggregated commit. Adding support vector machine for outlier detection, improve user interface to dry/live, better standardization, fix various other bugs 2022-05-22 17:51:49 +02:00
robcaulk
d1d451c27e auto populate features based on a prepended % in the strategy (remove feature assignment from config). Update doc/constants/example strategy to reflect change 2022-05-17 18:15:03 +02:00
robcaulk
8664e8f9a3 create a prediction_models folder where basic prediction models can live (similar to optimize/hyperopt-loss. Update resolver/docs/and gitignore to accommodate change 2022-05-17 17:13:38 +02:00