| --- |
| language: en |
| tags: |
| - cryptocurrency |
| - bitcoin |
| - price-prediction |
| - machine-learning |
| - time-series |
| license: mit |
| --- |
| |
| # Bitcoin (BTC) Price Prediction Models |
|
|
| Trained ML models for predicting Bitcoin (BTC) cryptocurrency prices. |
|
|
| ## 📊 Model Performance |
|
|
| | Model | RMSE | MAE | |
| |-------|------|-----| |
| | Random Forest | 1942.9146 | 1605.7746 | |
| | Gradient Boosting | 1878.1814 | 1449.6249 | |
| | Linear Regression | 338.9834 | 261.3517 | |
| | LSTM | 22511.9064 | 21610.0176 | |
|
|
| ## 🎯 Training Details |
|
|
| - **Trained on**: 2025-10-24 07:42:29 |
| - **Data Source**: CoinGecko API |
| - **Historical Days**: 365 |
| - **Features**: 23 technical indicators |
| - **GPU**: Accelerated with TensorFlow |
|
|
| ## 📦 Files Included |
|
|
| - `bitcoin_sklearn_models.pkl`: Scikit-learn models (RF, GB, LR) |
| - `bitcoin_scaler.pkl`: Feature scaler |
| - `bitcoin_lstm_model.h5`: LSTM neural network |
| - `bitcoin_metadata.json`: Training metadata |
|
|
| ## 🚀 Usage |
|
|
| ```python |
| from huggingface_hub import hf_hub_download |
| import joblib |
| from tensorflow.keras.models import load_model |
| |
| # Download models |
| sklearn_path = hf_hub_download( |
| repo_id="YOUR_USERNAME/YOUR_REPO", |
| filename="bitcoin_sklearn_models.pkl" |
| ) |
| scaler_path = hf_hub_download( |
| repo_id="YOUR_USERNAME/YOUR_REPO", |
| filename="bitcoin_scaler.pkl" |
| ) |
| lstm_path = hf_hub_download( |
| repo_id="YOUR_USERNAME/YOUR_REPO", |
| filename="bitcoin_lstm_model.h5" |
| ) |
| |
| # Load models |
| models = joblib.load(sklearn_path) |
| scaler = joblib.load(scaler_path) |
| lstm = load_model(lstm_path) |
| |
| # Make predictions |
| # (prepare your features first) |
| predictions = models['RandomForest'].predict(scaled_features) |
| ``` |
|
|
| ## 📈 Features |
|
|
| The models use 23 technical indicators including: |
| - Moving Averages (SMA 7, 25, 99) |
| - Exponential Moving Averages (EMA 12, 26) |
| - RSI (Relative Strength Index) |
| - MACD & Signal Line |
| - Bollinger Bands |
| - Stochastic Oscillator |
| - Volatility measures |
| - Lag features |
|
|
| ## ⚠️ Disclaimer |
|
|
| These models are for educational and research purposes only. Cryptocurrency markets are highly volatile and unpredictable. Do not use these predictions for actual trading decisions without proper risk management. |
|
|
| ## 📄 License |
|
|
| MIT License |
|
|
