Machine learning via multiresolution approximation

被引：0

作者：

Blayvas, I ^{[1
]}

Kimmel, R ^{[1
]}

机构：

[1] Technion Israel Inst Technol, Fac Comp Sci, Dept Comp Sci, IL-32000 Haifa, Israel

来源：

IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS | 2003年 / E86D卷 / 07期

关键词：

multiresolution approximation; machine learning; classification; regression estimation;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

We consider the classification problem as a problem of approximation of a given training set. This approximation is constructed in a multiresolution framework, and organized in a tree-structure. It allows efficient training and query, both in constant time per training point. The proposed method is efficient for low-dimensional classification and regression estimation problems with large data sets.

引用

页码：1172 / 1180

页数：9

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