| | --- |
| | language: en |
| | tags: |
| | - cryptocurrency |
| | - avalanche-2 |
| | - price-prediction |
| | - machine-learning |
| | - time-series |
| | license: mit |
| | --- |
| | |
| | # Avalanche (AVAX) Price Prediction Models |
| |
|
| | Trained ML models for predicting Avalanche (AVAX) cryptocurrency prices. |
| |
|
| | ## 📊 Model Performance |
| |
|
| | | Model | RMSE | MAE | |
| | |-------|------|-----| |
| | | Random Forest | 3.4884 | 2.6127 | |
| | | Gradient Boosting | 3.4596 | 2.5281 | |
| | | Linear Regression | 0.3193 | 0.1963 | |
| | | LSTM | 8.4368 | 7.3438 | |
| |
|
| | ## 🎯 Training Details |
| |
|
| | - **Trained on**: 2025-10-24 07:46:21 |
| | - **Data Source**: CoinGecko API |
| | - **Historical Days**: 365 |
| | - **Features**: 23 technical indicators |
| | - **GPU**: Accelerated with TensorFlow |
| |
|
| | ## 📦 Files Included |
| |
|
| | - `avalanche-2_sklearn_models.pkl`: Scikit-learn models (RF, GB, LR) |
| | - `avalanche-2_scaler.pkl`: Feature scaler |
| | - `avalanche-2_lstm_model.h5`: LSTM neural network |
| | - `avalanche-2_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="avalanche-2_sklearn_models.pkl" |
| | ) |
| | scaler_path = hf_hub_download( |
| | repo_id="YOUR_USERNAME/YOUR_REPO", |
| | filename="avalanche-2_scaler.pkl" |
| | ) |
| | lstm_path = hf_hub_download( |
| | repo_id="YOUR_USERNAME/YOUR_REPO", |
| | filename="avalanche-2_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 |
| |
|
