| 保持分类能力不变的一种连续属性离散化方法 |
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| 引用本文： | 巩建闽,王国胜,萧蓓蕾.保持分类能力不变的一种连续属性离散化方法[J].曲阜师范大学学报,2005,31(1):95-99. |
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| 作者姓名： | 巩建闽 王国胜 萧蓓蕾 |
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| 作者单位： | 德州学院计算机系，德州学院计算机系，德州学院计算机系 253023，山东省德州市，253023，山东省德州市，253023，山东省德州市 |
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| 基金项目： | 德州学院科研计划资助 (0 2 0 18) |
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| 摘 要： | 连续型属性的离散化问题是机器学习中的关键问题，是一个NP难题．该文针对决策表，在NaiveScaler算法的基础上，给出了一种直观、有效和易于理解的离散化方法．该方法从整个属性空间的角度来考虑属性的离散化问题，可有效地保证决策表中原有分类结果的不变性．
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| 关 键 词： | 分类 决策表 连续取值属性 离散化 |
| 文章编号： | 1001-5337(2005)01-0095-05 |
An Algorithm for Discretization of Continuous Type of Attributes which Keeps Classification Property Invariant |
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| GONG Jian-min,WANG Guo-sheng,XIAO Bei-lei.An Algorithm for Discretization of Continuous Type of Attributes which Keeps Classification Property Invariant[J].Journal of Qufu Normal University(Natural Science),2005,31(1):95-99. |
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| Authors: | GONG Jian-min WANG Guo-sheng XIAO Bei-lei |
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| Abstract: | Discretization of continuous type of attributes is a key issue in machine learning, it is a NP puzzle. This paper, aiming at decision tables, presents an effective and easily understandable discretization method based on Naive Scaler algorithm. it considers simultaneously, not separately, all attributes in decision tables, consequently, the break-points obtained are much less than that obtained by Naive Scaler algorithm, while the original classification property of the decision table keeps invariant. |
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| Keywords: | classification decision tables continuous type of attributes discretization |
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