Let Us Use Negative Examples in Regression-Type Problems Too

被引:0
|
作者
Contretas, Jonatan [1 ]
Zapata, Francisco [2 ]
Kosheleva, Olga [3 ]
Kreinovich, Vladik [1 ]
Ceberio, Martine [1 ]
机构
[1] Univ Texas El Paso, Dept Comp Sci, 500 W Univ, El Paso, TX 79968 USA
[2] Univ Texas El Paso, Dept Ind Mfg & Syst Engn, 500 W Univ, El Paso, TX 79968 USA
[3] Univ Texas El Paso, Dept Teacher Educ, 500 W Univ, El Paso, TX 79968 USA
基金
美国国家科学基金会;
关键词
Negative examples; regression; interval uncertainty; fuzzy uncertainty; probabilistic uncertainty;
D O I
10.1109/IV51561.2020.00055
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In many practical situations, we need to reconstruct the dependence between quantities x and y based on several situations in which we know both x and y values. Such problems are known as regression problems. Usually, this reconstruction is based on positive examples, when we know y - at least, with some accuracy. However, in addition, we often also know some examples in which we have negative information about y - e.g., we know that y does not belong to a certain interval. In this paper, we show how such negative examples can be used to make the solution to a regression problem more accurate.
引用
收藏
页码:296 / 300
页数:5
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