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ORCIDRobert S. Lynch Jr.
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2000 – 2009
- 2009
[c17]Robert S. Lynch Jr., Peter K. Willett
:
Estimating the threshold for maximizing expected gain in supervised discrete Bayesian classification. Data Mining, Intrusion Detection, Information Security and Assurance, and Data Networks Security 2009: 734408- [c16]Robert S. Lynch Jr., Peter K. Willett:
Maximizing expected gain in supervised discrete Bayesian classification when fusing binary valued features. FUSION 2009: 211-216 - 2008
- [c15]Dan Patterson, David A. Turner, Arturo I. Concepcion, Robert S. Lynch Jr.:
Performance comparison of the automatic data reduction system (ADRS). Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2008: 69730H - [c14]Tao Qian, Genshe Chen, Erik Blasch, Robert S. Lynch Jr., Yongwei Qi:
A new approach to chemical agent detection, classification, and estimation. Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2008: 69730K - [c13]Nicholas Navaroli, David A. Turner, Arturo I. Concepcion, Robert S. Lynch Jr.:
Performance Comparison of ADRS and PCA as a Preprocessor to ANN for Data Mining. ISDA (1) 2008: 47-52 - 2007
- [c12]Robert S. Lynch Jr., Peter K. Willett:
Mining unknown patterns in data when the features are correlated. Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2007: 657008 - 2006
- [c11]Robert S. Lynch Jr., Peter K. Willett:
An algorithmic approach to mining unknown clusters in training data. Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2006: 624101 - [c10]Robert S. Lynch Jr., Peter K. Willett:
Utilizing Fused Features to Mine Unknown Clusters in Training Data. FUSION 2006: 1-7 - 2005
- [c9]Robert S. Lynch Jr., Peter K. Willett:
Utilizing unsupervised learning to cluster data in the Bayesian data reduction algorithm. Data Mining, Intrusion Detection, Information Assurance, and Data Networks Security 2005: 158-167 - [c8]Robert S. Lynch Jr., Peter K. Willett:
A theoretical performance analysis of the Bayesian data reduction algorithm. SMC 2005: 330-335 - 2004
- [c7]Robert S. Lynch Jr., Peter K. Willett:
Quantizing features independently in the Bayesian data reduction algorithm. SMC (2) 2004: 1336-1341 - 2003
- [j3]Robert S. Lynch Jr., Peter K. Willett:
Use of Bayesian data reduction for the fusion of legacy classifiers. Inf. Fusion 4(1): 23-34 (2003) - [j2]Robert S. Lynch Jr., Peter K. Willett:
Bayesian classification and feature reduction using uniform Dirichlet priors. IEEE Trans. Syst. Man Cybern. Part B 33(3): 448-464 (2003) - [c6]Robert S. Lynch Jr., Peter K. Willett:
Classifier fusion results using various open literature data sets. SMC 2003: 723-728 - 2002
- [c5]Sun Yan, Peter Willett, Robert S. Lynch Jr.:
Waveform fusion for sonar detection and estimation. ICASSP 2002: 2973-2976 - 2001
- [c4]Robert S. Lynch Jr., Peter K. Willett:
Classification performance of various real-life data sets when the features are discretized. SMC 2001: 753-758 - 2000
- [c3]Robert S. Lynch Jr., Peter K. Willett:
Adaptive Bayesian classification using noninformative Dirichlet priors. SMC 2000: 2812-2815
1990 – 1999
- 1999
- [j1]Robert S. Lynch Jr., Peter K. Willett:
Performance considerations for a combined information classification test using Dirichlet priors. IEEE Trans. Signal Process. 47(6): 1711-1714 (1999) - [c2]Robert S. Lynch Jr., Peter K. Willett:
Classification using Dirichlet priors when the training data are mislabeled. ICASSP 1999: 2973-2976 - 1996
- [c1]Robert S. Lynch Jr., Peter Willett:
Classification with a combined information test. ICASSP 1996: 3061-3064
Coauthor Index
aka: Peter K. Willett
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