We provide improved estimates on the fat-shattering dimension of the $k$-fold maximum of real-valued function classes. The latter consists of all ways of choosing $k$ functions, one from each of the $k$ classes, and computing their pointwise maximum. The bound is stated in terms of the fat-shattering dimensions of the component classes. For linear and affine function classes, we provide a considerably sharper upper bound and a matching lower bound, achieving, in particular, an optimal dependence on $k$. Along the way, we point out and correct a number of erroneous claims in the literature.
翻译:我们改进了实际价值值功能类别最大值为1美元乘以1美元的最大值的脂肪挥发维度的估计数,后者包括选择1美元功能的各种方法,每个美元类别各一个,并计算其点性最大值,其约束以组成部分类别中脂肪挥发维度表示,对于线性功能和线性功能类别,我们提供了相当高的上限和相匹配的较低约束值,特别是实现了对1美元的最佳依赖。此外,我们指出并纠正文献中的一些错误主张。