# Class Imbalance Evaluation Protocol

The Clarus benchmark includes datasets with varying class distributions.

These datasets test whether models rely on prevalence rather than stability reasoning.

## Imbalance Regimes

### Balanced

50% stable  
50% unstable

### Mild Imbalance

70% stable  
30% unstable

### Severe Imbalance

90% stable  
10% unstable

### Extreme Imbalance

99% stable  
1% unstable

## Purpose

These datasets evaluate model robustness when instability events are rare.

This reflects real-world systems where collapse events are infrequent.

## Evaluation

The prediction task remains unchanged.

Performance should be evaluated using:

- precision
- recall
- F1 score

Accuracy alone is insufficient for highly imbalanced datasets.