Mining multi-dimensional data for decision support

被引：15
|
作者：
Donato, JM
Schryver, JC
Hinkel, GC
Schmoyer, RL
Leuze, MR [1 ]
Grandy, NW
机构：
[1] Oak Ridge Natl Lab, Oak Ridge, TN 37831 USA
[2] Joint Inst Computat Sci, Knoxville, TN 37996 USA
来源：
FUTURE GENERATION COMPUTER SYSTEMS | 1999年 / 15卷 / 03期
关键词：
data mining; personal bankruptcy; decision trees; partially recurrent neural networks;
D O I：
10.1016/S0167-739X(98)00086-7
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Personal bankruptcy is an increasingly common yet little understood phenomenon. Attempts to predict bankruptcy have involved the application of data mining techniques to credit card data. This is a difficult problem, since credit card data is multi-dimensional, consisting of monthly account records and daily transaction records. In this paper, we describe a two-stage approach that combines decision trees and neural networks to predict personal bankruptcy using credit card data. (C) 1999 Elsevier Science B.V. All rights reserved.
引用
收藏
页码：433 / 441
页数：9
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