Theoretical Measures of Relative Performance of Classifiers for High Dimensional Data with Small Sample Sizes
高维小样本分类器相对表现的理论度量
Summary We suggest a technique, related to the concept of ‘detection boundary’ that was developed by Ingster and by Donoho and Jin, for comparing the theoretical performance of classifiers constructed from small training samples of very large vectors. The resulting ‘classification boundaries’ are obtained for a variety of distance-based methods, including the support vector machine, distance-weighted discrimination and kth-nearest-neighbour classifiers, for thresholded forms…