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ML Algorithm Interpretability Matrix
Matrix 1 of 16| Algorithm | Model Type | The Memory Hack / Hint | Key Exam Triggers | Interpretability |
|---|---|---|---|---|
| Decision Trees | Rule-Based Splitter | Flowchart. A literal tree of If/Then branches that anyone can read. | Highly interpretable, clear insights, visual logic, explainability. | Highest |
| Logistic Regression | Linear Boundary | Straight Line. Separates data points into two clear sides (0 or 1). | Binary outcomes, simple baseline, probabilistic odds. | High |
| SVM | Hyperplane Margin | The Boundary Wall. Finding a perfect spatial wall between groups. | High-dimensional data, custom kernels, complex tabular splits. | Medium |
| Neural Networks | Deep Node Layers | Black Box. A giant mesh of artificial neurons doing heavy calculations. | Deep learning, complex relationships, large scale, hard to interpret. | Lowest |