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Applying Machine Learning to Semiconductor Manufacturing
February 1993 (vol. 8 no. 1)
pp. 41-47
ASCII Text
x 
 
Keki B. Irani, Jie Cheng, Usama M. Fayyad, Zhaogang Qian, "Applying Machine Learning to Semiconductor Manufacturing," IEEE Intelligent Systems, vol. 8, no. 1, pp. 41-47, February, 1993.
 
 
BibTex
x
 
@article{ 10.1109/64.193054,
author = {Keki B. Irani and Jie Cheng and Usama M. Fayyad and Zhaogang Qian},
title = {Applying Machine Learning to Semiconductor Manufacturing},
journal ={IEEE Intelligent Systems},
volume = {8},
number = {1},
issn = {0885-9000},
year = {1993},
pages = {41-47},
doi = {http://doi.ieeecomputersociety.org/10.1109/64.193054},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - MGZN
JO - IEEE Intelligent Systems
TI - Applying Machine Learning to Semiconductor Manufacturing
IS - 1
SN - 0885-9000
SP41
EP47
EPD - 41-47
A1 - Keki B. Irani,
A1 - Jie Cheng,
A1 - Usama M. Fayyad,
A1 - Zhaogang Qian,
PY - 1993
VL - 8
JA - IEEE Intelligent Systems
ER -
 

The generalized ID3 (GID3) algorithm, which takes a training set of experimental data and produces a decision tree that predicts the outcome of future experiments under various, more general conditions, is described. The tree can then be translated into a set of rules for an expert system. Two extensions to GID3MmRIST, and KARSM-that deal with the problems of noisy data and the limited availability of training data are discussed. The application of GID3 to reactive ion etching manufacturing process diagnosis and optimization and to knowledge acquisition for an expert system is described.

Citation:
Keki B. Irani, Jie Cheng, Usama M. Fayyad, Zhaogang Qian, "Applying Machine Learning to Semiconductor Manufacturing," IEEE Intelligent Systems, vol. 8, no. 1, pp. 41-47, Feb. 1993, doi:10.1109/64.193054
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