The management and mining of multiple predictive models using the predictive modeling markup language

被引:29
作者
Grossman, R
Bailey, S
Ramu, A
Malhi, B
Hallstrom, P
Pulleyn, I
Qin, X
机构
[1] Univ Illinois, Natl Ctr Data Min, Chicago, IL 60607 USA
[2] Magnify Inc, Chicago, IL 60606 USA
关键词
data mining; predictive modeling; data interchange formats; XML; SGML; ensemble learning; partitioned learning; distributed learning;
D O I
10.1016/S0950-5849(99)00022-1
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
We introduce a markup language based upon XML for working with the predictive models produced by data mining systems. The language is called the predictive model markup language (PMML) and can be used to define predictive models and ensembles of predictive models. It provides a flexible mechanism for defining schema for predictive models and supports model selection and model averaging, involving multiple predictive models. It has proved useful for applications requiring ensemble learning, partitioned learning and distributed learning. In addition, it facilitates moving predictive models across applications and systems. (C) 1999 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:589 / 595
页数:7
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