linreg-core 0.8.1

Lightweight regression library (OLS, Ridge, Lasso, Elastic Net, WLS, LOESS, Polynomial) with 14 diagnostic tests, cross validation, and prediction intervals. Pure Rust - no external math dependencies. WASM, Python, FFI, and Excel XLL bindings.
Documentation 
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<!DOCTYPE html>
<html lang="en">
<head>
  <meta charset="UTF-8">
  <title>Cross Validation — linreg-core WASM</title>
  <style>
    body { font-family: monospace; max-width: 780px; margin: 2rem auto; padding: 0 1rem; }
    h1   { font-size: 1.3rem; border-bottom: 2px solid #333; padding-bottom: 0.3rem; }
    pre  { background: #f5f5f5; padding: 1rem; border-radius: 4px; }
  </style>
</head>
<body>
  <h1>K-Fold Cross Validation — linreg-core WASM</h1>
  <p>5-fold CV comparing OLS, Ridge (λ=0.5), Lasso (λ=0.1), and Elastic Net (λ=0.2, α=0.5).</p>
  <pre id="output">Loading WASM…</pre>

  <script type="module">
    import init, {
      kfold_cv_ols,
      kfold_cv_ridge,
      kfold_cv_lasso,
      kfold_cv_elastic_net,
    } from 'https://unpkg.com/linreg-core/linreg_core.js';
    await init();

    // y = 1 + 2*x1 + 0.5*x2 + noise, n=20
    const n  = 20;
    const x1 = Array.from({length: n}, (_, i) => i + 1);
    const x2 = x1.map(x => x * 0.8 + (Math.random() - 0.5));  // correlated with x1
    const y  = x1.map((x, i) => 1 + 2 * x + 0.5 * x2[i] + (Math.random() * 2 - 1));

    const yJson  = JSON.stringify(y);
    const xJson  = JSON.stringify([x1, x2]);
    const names  = JSON.stringify(['Intercept', 'X1', 'X2']);

    // kfold_cv_ols:         (y, x, names, n_folds, shuffle_json, seed_json)
    // kfold_cv_ridge:       (y, x, lambda, standardize:bool, n_folds, shuffle_json, seed_json)
    // kfold_cv_lasso:       (y, x, lambda, standardize:bool, n_folds, shuffle_json, seed_json)
    // kfold_cv_elastic_net: (y, x, lambda, alpha, standardize:bool, n_folds, shuffle_json, seed_json)
    const ols  = JSON.parse(kfold_cv_ols(yJson, xJson, names, 5, 'true', '42'));
    const rdg  = JSON.parse(kfold_cv_ridge(yJson, xJson, 0.5, true, 5, 'true', '42'));
    const lso  = JSON.parse(kfold_cv_lasso(yJson, xJson, 0.1, true, 5, 'true', '42'));
    const enet = JSON.parse(kfold_cv_elastic_net(yJson, xJson, 0.2, 0.5, true, 5, 'true', '42'));

    console.log('ols', ols, 'ridge', rdg, 'lasso', lso, 'enet', enet);

    const f4 = v => (v != null ? Number(v).toFixed(4) : '—');

    const lines = [];
    lines.push(`n=${ols.n_samples}  folds=${ols.n_folds}  shuffle=true  seed=42`);
    lines.push('');

    // ── Summary table ────────────────────────────────────────────────────────
    lines.push('━━━ CV Summary ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━');
    lines.push('Metric           OLS       Ridge(0.5)  Lasso(0.1)  ENet(0.2,0.5)');
    lines.push('─'.repeat(68));

    const metricRow = (label, fn) =>
      label.padEnd(16) +
      f4(fn(ols)).padStart(9)  + '  ' +
      f4(fn(rdg)).padStart(10) + '  ' +
      f4(fn(lso)).padStart(10) + '  ' +
      f4(fn(enet)).padStart(13);

    lines.push(metricRow('Mean RMSE',   r => r.mean_rmse));
    lines.push(metricRow('Std RMSE',    r => r.std_rmse));
    lines.push(metricRow('Mean MAE',    r => r.mean_mae));
    lines.push(metricRow('Std MAE',     r => r.std_mae));
    lines.push(metricRow('Mean R²',     r => r.mean_r_squared));
    lines.push(metricRow('Std R²',      r => r.std_r_squared));
    lines.push(metricRow('Train R²',    r => r.mean_train_r_squared));

    // ── OLS fold detail ──────────────────────────────────────────────────────
    lines.push('');
    lines.push('━━━ OLS Fold Detail ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━');
    lines.push('Fold  Train  Test    RMSE      MAE       R²     Train R²');
    lines.push('─'.repeat(58));
    ols.fold_results.forEach(f => {
      lines.push(
        String(f.fold_index).padStart(4) + '  ' +
        String(f.train_size).padStart(5) + '  ' +
        String(f.test_size).padStart(4) + '  ' +
        f4(f.rmse).padStart(8) + '  ' +
        f4(f.mae).padStart(8) + '  ' +
        f4(f.r_squared).padStart(7) + '  ' +
        f4(f.train_r_squared).padStart(8)
      );
    });

    // ── Coefficient stability ─────────────────────────────────────────────────
    lines.push('');
    lines.push('━━━ OLS Coefficient Stability Across Folds ━━━━━━━━━━━━━━━━━━━━━━━━━');
    lines.push('Fold  Intercept       X1        X2');
    lines.push('─'.repeat(44));
    ols.fold_coefficients.forEach((coefs, i) => {
      lines.push(
        String(i + 1).padStart(4) + '  ' +
        coefs.map(c => f4(c).padStart(10)).join('  ')
      );
    });

    document.getElementById('output').textContent = lines.join('\n');
  </script>
</body>
</html>