optimiz-rs/docs/source/algorithms/sparse_optimization.md

Sparse Optimization

Sparse PCA and Elastic Net utilities with Rust speed.

Sparse PCA

import numpy as np
from optimizr import sparse_pca_py

X = np.random.randn(500, 20)
components = sparse_pca_py(X, n_components=5, l1_ratio=0.15)
print(components.shape)  # (5, 20)

Elastic Net

import numpy as np
from optimizr import elastic_net_py

X = np.random.randn(200, 8)
y = np.random.randn(200)
coeffs = elastic_net_py(X, y, l1_ratio=0.3, alpha=0.01)
print(coeffs)

Notes

• Inputs should be NumPy arrays; data is copied to Rust.
• l1_ratio balances sparsity vs ridge penalty.
• Standardize features before calling for stable solutions.