
MULTI-CROP DINO REPRESENTATION ANALYSIS REPORT
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DATASET SUMMARY:
- Total samples: 73
- Feature dimension: 512
- Number of classes: 6
- Class distribution: {np.int64(0): np.int64(18), np.int64(1): np.int64(15), np.int64(2): np.int64(9), np.int64(3): np.int64(7), np.int64(4): np.int64(10), np.int64(5): np.int64(14)}

DIMENSIONALITY REDUCTION:
- PCA components: 50 (if applicable)
- Explained variance: 0.998

CLUSTERING RESULTS:
- Algorithm: K-means
- Number of clusters: 6

QUALITY METRICS:
- Adjusted Rand Index (ARI): 0.5514
- Normalized Mutual Information (NMI): 0.7043
- Silhouette Score: 0.1832

INTERPRETATION:
- ARI measures agreement between true and predicted clusters
  * > 0.7: Excellent clustering
  * > 0.4: Good clustering  
  * > 0.1: Fair clustering
  * < 0.1: Poor clustering

- Current ARI of 0.551 indicates: GOOD performance

CONCLUSION:
DINO successfully learned meaningful representations that capture class structure.

Generated by Multi-Crop DINO implementation
