lolong
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9c051958a6
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Feat/freqai (#7105)
Vectorize weight setting, log training dates
Co-authored-by: robcaulk <rob.caulk@gmail.com>
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2022-07-19 17:49:18 +02:00 |
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lolong
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ed0f8b1189
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Improve FreqAI documentation (#7072)
Improve doc + some other small fixes
Co-authored-by: robcaulk <rob.caulk@gmail.com>
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2022-07-18 11:57:52 +02:00 |
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robcaulk
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4141d165ff
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add BaseTensorFlowModel class
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2022-07-12 19:10:09 +02:00 |
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robcaulk
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ef409dd345
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Add ground work for TensorFlow models, add protections from common mistakes
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2022-07-12 18:09:17 +02:00 |
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Robert Caulk
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fea63fba12
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Fix saving/loading historic predictions
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2022-07-12 10:12:50 +02:00 |
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Robert Caulk
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8ce6b18318
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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.
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2022-07-11 22:01:48 +02:00 |
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Matthias
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3fc92b1b21
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Create BaseRegression model - designed to reduce code duplication across currently available models.
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2022-07-11 11:33:59 +02:00 |
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Robert Caulk
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607455919e
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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!!)
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2022-07-10 12:35:44 +02:00 |
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Matthias
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819cc9c0e4
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Fully align LightGBM with Catboost
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2022-07-10 11:06:18 +02:00 |
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Matthias
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58b18770e3
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Fix LightGBM missing argument in predict method
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2022-07-10 11:05:35 +02:00 |
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Matthias
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2e1061af64
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Fix faulty LightGBM model
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2022-07-09 08:21:42 +00:00 |
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robcaulk
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8ac8d53c32
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All LGBMRegressor model parameters are now set in config
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2022-07-03 16:30:01 +02:00 |
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robcaulk
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ffb39a5029
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black formatting on freqai files
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2022-07-03 10:59:38 +02:00 |
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robcaulk
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106131ff0f
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Rehaul organization of return values
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2022-07-02 18:09:38 +02:00 |
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robcaulk
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051b99791d
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reduce unnecessary verbosity, fix error on first training sweep, add LightGBMPredictionModel
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2022-06-26 19:04:23 +02:00 |
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robcaulk
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f631ae911b
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add model expiration feature, fix bug in DI return values
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2022-06-17 14:55:40 +02:00 |
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robcaulk
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c5de0c49e4
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first functional scanning commit
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2022-06-16 00:24:18 +02:00 |
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Matthias
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c981ad4608
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Fix missing space
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2022-06-12 08:31:02 +02:00 |
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robcaulk
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15d049cffe
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detect if upper tf candles are new or not, append if so. Correct the epoch for candle update check
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2022-06-07 19:49:20 +02:00 |
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robcaulk
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f2762e3b4b
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fix bug in return_values()
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2022-06-03 16:58:51 +02:00 |
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robcaulk
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16b4a5b71f
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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.
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2022-06-03 15:19:46 +02:00 |
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robcaulk
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c5a16e91fb
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throw user error if user tries to load models but feeds the wrong features (while using PCA)
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2022-05-28 11:11:41 +02:00 |
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robcaulk
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6193205012
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fix bug for target_mean/std array merging in backtesting
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2022-05-26 21:07:50 +02:00 |
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robcaulk
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255d35976e
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add priority metadata to pairs to avoid a sync of train time + train period
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2022-05-24 12:58:53 +02:00 |
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robcaulk
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059c285425
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paying closer attention to managing live retraining on separate thread without affecting prediction of other coins on master thread
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2022-05-24 12:01:01 +02:00 |
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robcaulk
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b0d2d13eb1
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improve data persistence/mapping for live/dry. This accommodates quick reloads after crash and handles multi-pair cleanly
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2022-05-23 21:05:05 +02:00 |
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robcaulk
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e1c068ca66
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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.
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2022-05-23 12:07:09 +02:00 |
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robcaulk
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af0cc21af9
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Enable hourly/minute retraining in live/dry. Suppress catboost folder output. Update config + constants + docs to reflect updates.
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2022-05-23 00:06:26 +02:00 |
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robcaulk
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42d95af829
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Aggregated commit. Adding support vector machine for outlier detection, improve user interface to dry/live, better standardization, fix various other bugs
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2022-05-22 17:51:49 +02:00 |
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robcaulk
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d1d451c27e
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auto populate features based on a prepended % in the strategy (remove feature assignment from config). Update doc/constants/example strategy to reflect change
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2022-05-17 18:15:03 +02:00 |
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robcaulk
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8664e8f9a3
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create a prediction_models folder where basic prediction models can live (similar to optimize/hyperopt-loss. Update resolver/docs/and gitignore to accommodate change
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2022-05-17 17:13:38 +02:00 |
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