The main results are elaborated as follows.1. When the category members had the same features across two near dimensions , the classification learning and the inference learning was advanced.2.
类别内的成员具有双维度匹配特征,或者在双维度分离特征位置上具有双维度相同特征关系时,对于分类学习和推理学习不能起到这种特定的促进作用。
参考来源 - 双维度特征关系和特征位置对类别学习的影响·2,447,543篇论文数据，部分数据来源于NoteExpress
Classification Learning is the important content in Machine Learning.
分类学习是机器学习重要的研究内容。
Digit recognition, once again, is a common example of classification learning.
数字识别再一次成为分类学习的常见样本。
Classification learning is often necessary when the decisions made by the algorithm will be required as input somewhere else.
如果通过算法作出的决定需要输入别的地方，这时分类学习是必要的。
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