5. Model Selection

• 5.1. Cross-Validation
  • 5.1.1. Examples
  • 5.1.2. Cross validation iterators
    • 5.1.2.1. Leave-One-Out - LOO
    • 5.1.2.2. Leave-P-Out - LPO
    • 5.1.2.3. K-fold
    • 5.1.2.4. Stratified K-Fold
    • 5.1.2.5. Leave-One-Label-Out - LOLO
    • 5.1.2.6. Leave-P-Label-Out
    • 5.1.2.7. Random permutations cross-validation a.k.a. Shuffle & Split
    • 5.1.2.8. Bootstrapping cross-validation
  • 5.1.3. Computing cross-validated metrics
• 5.2. Grid Search
  • 5.2.1. Examples
  • 5.2.2. Alternatives to brute force grid search
    • 5.2.2.1. Model specific cross-validation
      • 9.2.3. sklearn.linear_model.RidgeCV
      • 5.2.2.1.2. sklearn.linear_model.RidgeClassifierCV
      • 9.2.10. sklearn.linear_model.LarsCV
      • 9.2.11. sklearn.linear_model.LassoLarsCV
      • 9.2.5. sklearn.linear_model.LassoCV
      • 9.2.7. sklearn.linear_model.ElasticNetCV
    • 5.2.2.2. Information Criterion
      • 9.2.12. sklearn.linear_model.LassoLarsIC