Freqtrade

Freqtrade stratejileri ve FreqAI modelleri, algoritma referansı

SampleStrategy (Freqtrade)

Template strategy demonstrating basic technical indicator usage for entry/exit signals. Kaynak: https://github.com/freqtrade/freqtrade/blob/develop/freqtrade/templates/sample_strategy.py.

LightGBMRegressor (Freqtrade)

Gradient boosting regression model for price movement prediction using LightGBM. Temel parametreler: n_estimators (Number of boosting rounds), learning_rate (Step size shrinkage).Kaynak: https://github.com/freqtrade/freqtrade/blob/develop/freqai/prediction_models/LightGBMRegressor.py.

LightGBMClassifier (Freqtrade)

Gradient boosting classification model for directional prediction (up/down/neutral). Temel parametreler: n_estimators (Number of boosting rounds).Kaynak: https://github.com/freqtrade/freqtrade/blob/develop/freqai/prediction_models/LightGBMClassifier.py.

XGBoostRegressor (Freqtrade)

XGBoost-based regression model for continuous value prediction. Temel parametreler: n_estimators (Number of boosting rounds), max_depth (Maximum tree depth).Kaynak: https://github.com/freqtrade/freqtrade/blob/develop/freqai/prediction_models/XGBoostRegressor.py.

XGBoostClassifier (Freqtrade)

XGBoost-based classification model for directional prediction. Temel parametreler: n_estimators (Number of boosting rounds).Kaynak: https://github.com/freqtrade/freqtrade/blob/develop/freqai/prediction_models/XGBoostClassifier.py.

CatboostRegressor (Freqtrade)

CatBoost gradient boosting model with native categorical feature support. Temel parametreler: iterations (Number of boosting iterations).Kaynak: https://github.com/freqtrade/freqtrade/blob/develop/freqai/prediction_models/CatboostRegressor.py.

PyTorchMLPRegressor (Freqtrade)

Multi-layer perceptron neural network for regression-based price prediction. Temel parametreler: hidden_dim (Hidden layer dimension), dropout_percent (Dropout rate).Kaynak: https://github.com/freqtrade/freqtrade/blob/develop/freqai/prediction_models/PyTorchMLPRegressor.py.

PyTorchTransformerRegressor (Freqtrade)

Transformer architecture for time-series regression using self-attention mechanism. Temel parametreler: num_heads (Number of attention heads), num_layers (Number of transformer layers).Kaynak: https://github.com/freqtrade/freqtrade/blob/develop/freqai/prediction_models/PyTorchTransformerRegressor.py.

ReinforcementLearner (Freqtrade)

Reinforcement learning agent using Stable Baselines3 (PPO/A2C/etc.) for trading decisions. Temel parametreler: model_type (RL algorithm (PPO, A2C, etc.)), total_timesteps (Training timesteps).Kaynak: https://github.com/freqtrade/freqtrade/blob/develop/freqai/prediction_models/ReinforcementLearner.py.