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Optimized Nearest Neighbor Methods Cam Weighted Distance vs. Statistical Confidence Robert R. Puckett.

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Presentation on theme: "Optimized Nearest Neighbor Methods Cam Weighted Distance vs. Statistical Confidence Robert R. Puckett."— Presentation transcript:

1 Optimized Nearest Neighbor Methods Cam Weighted Distance vs. Statistical Confidence Robert R. Puckett

2 Cam-Weighted Distance Deforms the distribution by transformation Simulates strengthening and weakening effects between prototypes. k-nearest neighbors used to estimate parameters of the distribution Inverse transform used to provide a “cam weighted distance”

3 Statistical Confidence Confidence proportional majority value of neighbors. On low confidence choose bigger k An alternative to globally increasing the k value. Algorithm selectively increases the k- value only when the confidence is below some threshold.

4 Goals Implement NN-Base System Cam-NN Add-on Statistical Confidence Add-on Create hybrid method Test against dataset

5 Schedule Main Milestones Software development Dataset generation Analysis Report Writing Schedule

6 References Duda, R. O., P. E. Hart, et al. (2001). Pattern classification. New York, Wiley. Wang, J., P. Neskovic, et al. (2006). "Neighborhood size selection in the k-nearest- neighbor rule using statistical confidence." Pattern Recognition 39 (3): 417-423. Zhou, C. Y. and Y. Q. Chen (2006). "Improving nearest neighbor classification with cam weighted distance." Pattern Recognition 39 (4): 635-645.

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