The continuous attribute problems are often encountered in the real world, but many outstanding inductive learning algorithms are mainly based on a discrete feature space.
实际问题中经常涉及连续的数值属性，然而许多归纳学习算法却是针对离散属性空间的。
First, the attribute of studies, theoretical research is different from applied study: the former requires data to be continuous in time and entire in space, but the latter demand the data to be new.
一是研究的属性问题，即理论研究和应用研究在资料利用方面的不同：理论研究要求数据资料的时间连续性和空间完整性，但对数据的现势性没有特别要求；
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