106 Commits

Author	SHA1	Message	Date
robcaulk	647200e8a7	isort	2022-09-23 19:30:56 +02:00
robcaulk	77c360b264	improve typing, improve docstrings, ensure global tests pass	2022-09-23 19:17:27 +02:00
robcaulk	ea8e34e192	Merge branch 'develop' into dev-merge-rl	2022-09-22 19:46:50 +02:00
robcaulk	8aac644009	add tests. add guardrails.	2022-09-15 00:46:35 +02:00
robcaulk	81417cb795	Merge branch 'develop' into dev-merge-rl	2022-09-14 22:49:11 +02:00
Emre	330d7068ab	Merge branch 'develop' into add-xgboostclassifier	2022-09-10 23:59:11 +03:00
robcaulk	5a0cfee27e	allow user to multithread jobs (advanced users only)	2022-09-10 22:16:49 +02:00
Emre	60eb02bb62	Add XGBoostClassifier	2022-09-10 20:13:16 +03:00
robcaulk	10b6aebc5f	enable continual learning and evaluation sets on multioutput models.	2022-09-10 16:54:13 +02:00
robcaulk	a826c0eb83	ensure signatures match, reduce verbosity	2022-09-09 19:30:53 +02:00
Emre	acb410a0de	Remove verbosity params	2022-09-09 19:30:53 +02:00
Emre	df6e43d2c5	Add XGBoostRegressorMultiTarget class	2022-09-09 19:30:53 +02:00
Emre	1b6410d7d1	Add XGBoostRegressor for freqAI, fix mypy errors	2022-09-09 19:30:53 +02:00
robcaulk	4c9ac6b7c0	add kwargs, reduce duplicated code	2022-09-07 18:58:55 +02:00
robcaulk	97077ba18a	add continual learning to catboost and friends	2022-09-06 20:30:46 +02:00
robcaulk	240b529533	fix tensorboard path so that users can track all historical models	2022-08-31 16:50:39 +02:00
robcaulk	7766350c15	refactor environment inheritence tree to accommodate flexible action types/counts. fix bug in train profit handling	2022-08-28 19:21:57 +02:00
robcaulk	3199eb453b	reduce code for base use-case, ensure multiproc inherits custom env, add ability to limit ram use.	2022-08-25 19:05:51 +02:00
robcaulk	05ccebf9a1	automate eval freq in multiproc	2022-08-25 12:29:48 +02:00
robcaulk	94cfc8e63f	fix multiproc callback, add continual learning to multiproc, fix totalprofit bug in env, set eval_freq automatically, improve default reward	2022-08-25 11:46:18 +02:00
robcaulk	d1bee29b1e	improve default reward, fix bugs in environment	2022-08-24 18:32:40 +02:00
robcaulk	bd870e2331	fix monitor bug, set default values in case user doesnt set params	2022-08-24 16:32:14 +02:00
robcaulk	c0cee5df07	add continual retraining feature, handly mypy typing reqs, improve docstrings	2022-08-24 13:00:55 +02:00
robcaulk	b708134c1a	switch multiproc thread count to rl_config definition	2022-08-24 13:00:55 +02:00
robcaulk	b26ed7dea4	fix generic reward, add time duration to reward	2022-08-24 13:00:55 +02:00
robcaulk	29f0e01c4a	expose environment reward parameters to the user config	2022-08-24 13:00:55 +02:00
robcaulk	3eb897c2f8	reuse callback, allow user to acces all stable_baselines3 agents via config	2022-08-24 13:00:55 +02:00
sonnhfit	4baa36bdcf	fix persist a single training environment for PPO	2022-08-24 13:00:55 +02:00
robcaulk	f95602f6bd	persist a single training environment.	2022-08-24 13:00:55 +02:00
robcaulk	5d4e5e69fe	reinforce training with state info, reinforce prediction with state info, restructure config to accommodate all parameters from any user imported model type. Set 5Act to default env on TDQN. Clean example config.	2022-08-24 13:00:55 +02:00
robcaulk	b90da46b1b	improve price df handling to enable backtesting	2022-08-24 13:00:55 +02:00
sonnhfit	0475b7cb18	remove unuse code and fix coding conventions	2022-08-24 13:00:55 +02:00
MukavaValkku	d60a166fbf	multiproc TDQN with xtra callbacks	2022-08-24 13:00:55 +02:00
robcaulk	dd382dd370	add monitor to eval env so that multiproc can save best_model	2022-08-24 13:00:55 +02:00
robcaulk	e5df39e891	ensuring best_model is placed in ram and saved to disk and loaded from disk	2022-08-24 13:00:55 +02:00
robcaulk	bf7ceba958	set cpu threads in config	2022-08-24 13:00:55 +02:00
MukavaValkku	57c488a6f1	learning_rate + multicpu changes	2022-08-24 13:00:55 +02:00
robcaulk	acf3484e88	add multiprocessing variant of ReinforcementLearningPPO	2022-08-24 13:00:55 +02:00
MukavaValkku	13cd18dc9a	PPO policy change + verbose=1	2022-08-24 13:00:55 +02:00
robcaulk	926023935f	make base 3ac and base 5ac environments. TDQN defaults to 3AC.	2022-08-24 13:00:55 +02:00
MukavaValkku	096533bcb9	3ac to 5ac	2022-08-24 13:00:55 +02:00
MukavaValkku	718c9d0440	action fix	2022-08-24 13:00:55 +02:00
robcaulk	9c78e6c26f	base PPO model only customizes reward for 3AC	2022-08-24 13:00:55 +02:00
robcaulk	6048f60f13	get TDQN working with 5 action environment	2022-08-24 13:00:55 +02:00
robcaulk	d4db5c3281	ensure TDQN class is properly named	2022-08-24 13:00:55 +02:00
robcaulk	91683e1dca	restructure RL so that user can customize environment	2022-08-24 13:00:55 +02:00
sonnhfit	ecd1f55abc	add rl module	2022-08-24 13:00:55 +02:00
MukavaValkku	9b895500b3	initial commit - new dev branch	2022-08-24 13:00:55 +02:00
MukavaValkku	cd3fe44424	callback function and TDQN model added	2022-08-24 13:00:55 +02:00
MukavaValkku	01232e9a1f	callback function and TDQN model added	2022-08-24 13:00:55 +02:00