Name
Title | ||
|---|---|---|
Minimizing Nearest Neighbor Classification Error for Nonparametric Dimension Reduction. |
Abstract | ||
|---|---|---|
In this brief, we show that minimizing nearest neighbor classification error (MNNE) is a favorable criterion for supervised linear dimension reduction (SLDR). We prove that MNNE is better than maximizing mutual information in the sense of being a proxy of the Bayes optimal criterion. Based on kernel density estimation, we derive a nonparametric algorithm for MNNE. Experiments on benchmark data set... |
Year | DOI | Venue |
|---|---|---|
2014 | 10.1109/TNNLS.2013.2294547 | IEEE Transactions on Neural Networks and Learning Systems |
Keywords | Field | DocType |
Bandwidth,Kernel,Training,Artificial neural networks,Manifolds,Entropy,Mutual information | k-nearest neighbors algorithm,Data set,Dimensionality reduction,Pattern recognition,Computer science,Nonparametric statistics,Mutual information,Artificial intelligence,Bayes error rate,Machine learning,Bayes' theorem,Kernel density estimation | Journal |
Volume | Issue | ISSN |
25 | 8 | 2162-237X |
Citations | PageRank | References |
1 | 0.36 | 10 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wei Bian | 1 | 475 | 24.88 |
| Tianyi Zhou | 2 | 413 | 28.68 |
| Aleix Martinez | 3 | 2374 | 143.45 |
| George Baciu | 4 | 409 | 56.17 |
| Dacheng Tao | 5 | 19032 | 747.78 |