论文信息 - Decision Tree Induction with CBR

Decision Tree Induction with CBR

This paper describes an application of CBR with decision tree induction in a manufacturing setting to analyze the cause for defects reoccurring in the domain. Abstraction of domain knowledge is made possible by integrating CBR with decision trees. The CID approach augments the recall and reuse done by CBR with statistical analysis that is focused towards the discovery of connections between specific defects and their possible causes. We show that this discovery also gives a pointer towards a corresponding corrective action.

Deepak Khemani | Radhika B. Selvamani | D. Khemani

[1] Alberto Maria Segre,et al. Programs for Machine Learning , 1994 .

[2] Deepak Khemani,et al. InfoFrax : CBR in Fused Cast Refractory Manufacture , 2002, ECCBR.

[3] David W. Aha,et al. Instance-Based Learning Algorithms , 1991, Machine Learning.

[4] Deepak Khemani,et al. Knowledge Management in Manufacturing Technology: An A.I. Application in the Industry , 2002, ICEIS.

[5] S. Salzberg,et al. A weighted nearest neighbor algorithm for learning with symbolic features , 2004, Machine Learning.

[6] Jiawei Han,et al. Data Mining: Concepts and Techniques , 2000 .

[7] Barry Smyth,et al. Advances in Case-Based Reasoning , 1996, Lecture Notes in Computer Science.

[8] Janet L. Kolodner,et al. Case-Based Reasoning , 1989, IJCAI 1989.

[9] Luc Lamontagne,et al. Case-Based Reasoning Research and Development , 1997, Lecture Notes in Computer Science.

[10] Deepak Khemani,et al. Managing Experience for Process Improvement in Manufacturing , 2003, ICCBR.

[11] Chris J. Price,et al. From Troubleshooting to Process Design: Closing the Manufacturing Loop , 1997, ICCBR.

[12] Ian D. Watson,et al. Applying case-based reasoning - techniques for the enterprise systems , 1997 .

[13] J. Ross Quinlan,et al. C4.5: Programs for Machine Learning , 1992 .