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

页码：433 / 441

页数：9

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