Data Mining and Knowledge Discovery

  1. Model Evaluation and Validation
    1. Evaluation Methodology
      1. Training, Validation, and Test Sets
        1. Cross-Validation Techniques
          1. K-Fold Cross-Validation
            1. Stratified Cross-Validation
              1. Leave-One-Out Cross-Validation
                1. Time Series Cross-Validation
                2. Bootstrap Methods
                  1. Holdout Validation
                  2. Classification Evaluation
                    1. Confusion Matrix Analysis
                      1. True Positives and Negatives
                        1. False Positives and Negatives
                          1. Multi-Class Confusion Matrices
                          2. Performance Metrics
                            1. Accuracy
                              1. Precision
                                1. Recall and Sensitivity
                                  1. Specificity
                                    1. F1-Score
                                      1. Matthews Correlation Coefficient
                                      2. ROC Analysis
                                        1. ROC Curve Construction
                                          1. Area Under the Curve
                                            1. ROC Space Interpretation
                                            2. Precision-Recall Analysis
                                              1. Precision-Recall Curves
                                                1. Average Precision
                                                  1. Break-Even Point
                                                  2. Cost-Sensitive Evaluation
                                                  3. Regression Evaluation
                                                    1. Error Metrics
                                                      1. Mean Absolute Error
                                                        1. Mean Squared Error
                                                          1. Root Mean Squared Error
                                                            1. Mean Absolute Percentage Error
                                                            2. Correlation Measures
                                                              1. Pearson Correlation
                                                                1. Spearman Correlation
                                                                2. Coefficient of Determination
                                                                  1. Residual Analysis
                                                                  2. Clustering Evaluation
                                                                    1. Internal Validation
                                                                      1. Within-Cluster Sum of Squares
                                                                        1. Silhouette Analysis
                                                                          1. Davies-Bouldin Index
                                                                            1. Dunn Index
                                                                            2. External Validation
                                                                              1. Rand Index
                                                                                1. Adjusted Rand Index
                                                                                  1. Normalized Mutual Information
                                                                                    1. Fowlkes-Mallows Index
                                                                                    2. Relative Validation
                                                                                    3. Statistical Significance Testing
                                                                                      1. Hypothesis Testing Framework
                                                                                        1. Paired t-Tests
                                                                                          1. McNemar's Test
                                                                                            1. Wilcoxon Signed-Rank Test
                                                                                              1. Multiple Comparison Corrections
                                                                                              2. Model Selection and Comparison
                                                                                                1. Information Criteria
                                                                                                  1. Akaike Information Criterion
                                                                                                    1. Bayesian Information Criterion
                                                                                                    2. Model Complexity Considerations
                                                                                                      1. Ensemble Model Evaluation
                                                                                                        1. Hyperparameter Optimization

                                                                                                      Previous

                                                                                                      8. Advanced Mining Techniques

                                                                                                      Go to top

                                                                                                      Next

                                                                                                      10. Model Interpretation and Explainability