Minimax Optimal High‐Dimensional Classification using Deep Neural Networks
Stat(2022)
摘要
High-dimensional classification is a fundamentally important research problem in high-dimensional data analysis. In this paper, we derive nonasymptotic rate for the minimax excess misclassification risk when feature dimension exponentially diverges with the sample size and the Bayes classifier possesses a complicated modular structure. We also show that classifiers based on deep neural network attain the above rate, hence, are minimax optimal.
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关键词
deep neural network, high-dimensional classification, minimax excess misclassification risk, modular structure
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