Machine Learning vs Rules Decision Boundary Playground

Class A (Rested / Safe)

Class B (Fatigued / Risk)

Add Point:

Dataset Preset

Classifier Engine Mode

ML Algorithm Model

Model Inspector

ML Optimization Hyperparameters

Learning Rate / Depth 0.05

Comparison & Accuracy
            ML Accuracy
            100%
          

            Rule Accuracy
            83.3%
          

Dynamic Decision Boundary Equation

0.62*Screen - 0.78*Sleep + 1.15 = 0

Conceptual Learning Verdict

Machine learning learned a continuous diagonal separation boundary that manual axis-aligned IF statements failed to capture cleanly.

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