Phyto Neural Architecture Search for Time Series Classification
Project description
Phyto-NAS-TSC
An evolutionary approach to automatically design optimal neural network architectures for time series classification tasks.
Installation
pip install phyto-nas-tsc
## Installation directly from source
git clone https://github.com/carmelyr/Phyto-NAS-T.git
cd Phyto-NAS-T
pip install -e .
## Features
- Evolutionary algorithm for architecture search
- Optimized for time series data (1D signals)
- Optimized for LSTM model
- Tracks optimization history and metrics
- GPU-accelerated training
## Quickstart
```python
import numpy as np
from phyto_nas_tsc import fit
# Synthetic data
X = np.random.rand(100, 10, 1)
y = np.eye(2)[np.random.randint(0, 2, 100)]
# Run optimization
results = fit(X, y, generations=3, population_size=5)
print(f"Best Architecture: {results['architecture']}")
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