Melvin Alvarez
32 lines
673 B
Markdown
32 lines
673 B
Markdown
# Sparse Optimization
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Sparse PCA and Elastic Net utilities with Rust speed.
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## Sparse PCA
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```python
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import numpy as np
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from optimizr import sparse_pca_py
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X = np.random.randn(500, 20)
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components = sparse_pca_py(X, n_components=5, l1_ratio=0.15)
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print(components.shape) # (5, 20)
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```
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## Elastic Net
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```python
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import numpy as np
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from optimizr import elastic_net_py
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X = np.random.randn(200, 8)
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y = np.random.randn(200)
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coeffs = elastic_net_py(X, y, l1_ratio=0.3, alpha=0.01)
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print(coeffs)
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```
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## Notes
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- Inputs should be NumPy arrays; data is copied to Rust.
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- `l1_ratio` balances sparsity vs ridge penalty.
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- Standardize features before calling for stable solutions.
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