Machine Learning

  1. Ensemble Methods and Advanced Techniques
    1. Ensemble Learning Principles
      1. Wisdom of Crowds
        1. Diversity in Ensemble
          1. Bias-Variance Decomposition for Ensembles
            1. Ensemble Size Considerations
            2. Bagging Methods
              1. Bootstrap Aggregating
                1. Bootstrap Sampling
                  1. Aggregation Strategies
                    1. Voting for Classification
                      1. Averaging for Regression
                      2. Variance Reduction
                        1. Parallel Training
                        2. Random Forests
                          1. Decision Tree Base Learners
                            1. Feature Bagging
                              1. Random Feature Selection
                                1. Feature Subset Size
                                2. Out-of-Bag Error Estimation
                                  1. OOB Score Calculation
                                    1. Model Evaluation Without Validation Set
                                    2. Feature Importance
                                      1. Gini Importance
                                        1. Permutation Importance
                                        2. Hyperparameter Tuning
                                          1. Number of Trees
                                            1. Tree Depth
                                              1. Feature Subset Size
                                              2. Advantages and Limitations
                                              3. Extra Trees
                                                1. Extremely Randomized Trees
                                                  1. Random Thresholds
                                                    1. Comparison with Random Forests
                                                  2. Boosting Methods
                                                    1. Boosting Principles
                                                      1. Sequential Learning
                                                        1. Weak Learner Combination
                                                          1. Adaptive Reweighting
                                                            1. Bias Reduction
                                                            2. AdaBoost
                                                              1. Algorithm Steps
                                                                1. Sample Weight Updates
                                                                  1. Weak Learner Weights
                                                                    1. Exponential Loss Function
                                                                      1. Theoretical Properties
                                                                      2. Gradient Boosting
                                                                        1. Gradient Boosting Framework
                                                                          1. Residual Fitting
                                                                            1. Gradient Descent in Function Space
                                                                              1. Learning Rate
                                                                                1. Regularization Techniques
                                                                                2. Gradient Boosting Machines
                                                                                  1. Tree-Based Weak Learners
                                                                                    1. Shrinkage Parameter
                                                                                      1. Subsampling
                                                                                        1. Feature Subsampling
                                                                                        2. XGBoost
                                                                                          1. Extreme Gradient Boosting
                                                                                            1. Second-Order Optimization
                                                                                              1. Regularization Terms
                                                                                                1. Parallel Processing
                                                                                                  1. Missing Value Handling
                                                                                                    1. Feature Importance
                                                                                                    2. LightGBM
                                                                                                      1. Gradient-Based One-Side Sampling
                                                                                                        1. Exclusive Feature Bundling
                                                                                                          1. Leaf-Wise Tree Growth
                                                                                                            1. Memory Efficiency
                                                                                                            2. CatBoost
                                                                                                              1. Categorical Feature Handling
                                                                                                                1. Ordered Boosting
                                                                                                                  1. Symmetric Trees
                                                                                                                    1. Overfitting Reduction
                                                                                                                    2. Handling Overfitting in Boosting
                                                                                                                      1. Early Stopping
                                                                                                                        1. Regularization Parameters
                                                                                                                          1. Cross-Validation Monitoring
                                                                                                                        2. Stacking and Blending
                                                                                                                          1. Stacked Generalization
                                                                                                                            1. Base Learners
                                                                                                                              1. Meta-Learner
                                                                                                                                1. Cross-Validation for Meta-Features
                                                                                                                                  1. Multi-Level Stacking
                                                                                                                                  2. Blending
                                                                                                                                    1. Holdout Set for Meta-Learning
                                                                                                                                      1. Comparison with Stacking
                                                                                                                                        1. Computational Efficiency
                                                                                                                                        2. Model Diversity
                                                                                                                                          1. Algorithm Diversity
                                                                                                                                            1. Data Diversity
                                                                                                                                              1. Parameter Diversity
                                                                                                                                              2. Meta-Learner Selection
                                                                                                                                                1. Linear Models
                                                                                                                                                  1. Non-Linear Models
                                                                                                                                                    1. Regularization in Meta-Learning
                                                                                                                                                  2. Voting Methods
                                                                                                                                                    1. Hard Voting
                                                                                                                                                      1. Majority Vote
                                                                                                                                                        1. Plurality Vote
                                                                                                                                                          1. Tie-Breaking Strategies
                                                                                                                                                          2. Soft Voting
                                                                                                                                                            1. Probability Averaging
                                                                                                                                                              1. Weighted Voting
                                                                                                                                                                1. Confidence-Based Weighting
                                                                                                                                                                2. Weighted Voting
                                                                                                                                                                  1. Performance-Based Weights
                                                                                                                                                                    1. Dynamic Weight Adjustment
                                                                                                                                                                  2. Hyperparameter Optimization
                                                                                                                                                                    1. Hyperparameter vs. Parameter Distinction
                                                                                                                                                                      1. Search Strategies
                                                                                                                                                                        1. Bayesian Optimization
                                                                                                                                                                          1. Gaussian Process Models
                                                                                                                                                                            1. Acquisition Functions
                                                                                                                                                                              1. Sequential Model-Based Optimization
                                                                                                                                                                              2. Evolutionary Algorithms
                                                                                                                                                                                1. Genetic Algorithms
                                                                                                                                                                                  1. Particle Swarm Optimization
                                                                                                                                                                                  2. Gradient-Based Methods
                                                                                                                                                                                    1. Differentiable Hyperparameters
                                                                                                                                                                                      1. Hypergradients
                                                                                                                                                                                    2. Multi-Fidelity Optimization
                                                                                                                                                                                      1. Successive Halving
                                                                                                                                                                                        1. Hyperband
                                                                                                                                                                                          1. BOHB
                                                                                                                                                                                          2. Early Stopping
                                                                                                                                                                                            1. Validation-Based Stopping
                                                                                                                                                                                              1. Patience Parameter
                                                                                                                                                                                                1. Restoration of Best Weights
                                                                                                                                                                                                2. Automated Machine Learning
                                                                                                                                                                                                  1. AutoML Frameworks
                                                                                                                                                                                                    1. Feature Engineering Automation
                                                                                                                                                                                                      1. Model Selection Automation

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                                                                                                                                                                                                  8. Deep Learning and Neural Networks