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Optimizing Nearest Neighbor Methods with Cam-Weighted Distance and Statistical Confidence

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This study explores the Cam-Weighted Distance, which alters the distribution through transformation, simulating effects between prototypes. By applying k-nearest neighbors (k-NN) to estimate distribution parameters, we introduce an inverse transform for calculating Cam-Weighted Distance. The method leverages statistical confidence to adjust neighbor values, selectively increasing k based on confidence levels. Our goal is to implement a robust NN-based system with an innovative Cam-NN add-on for statistical confidence. We aim to test against datasets and outline a comprehensive software development schedule with milestones for analysis and reporting.

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Optimizing Nearest Neighbor Methods with Cam-Weighted Distance and Statistical Confidence

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