一种示例式机器学习新算法

An Algorithm of Learning from Example

揭示了例子空间中存在的一些规律 ,并归结为若干定理 ,表明了只要考察少量的覆盖任一示例集的项便可计算出与该示例集相关的评价矩阵 ,从而避免了对逐个示例的扫描 。

Some rules of example space and expounds some theorems are revealed.It explains that we figure out suitable of example sets if only explore a small quantity of item of example sets, thereby, it avoids to scan to scan every example, and only save a small quantity of item not huge example stes.