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TKDE
2008
123views more  TKDE 2008»
14 years 11 months ago
Explaining Classifications For Individual Instances
We present a method for explaining predictions for individual instances. The presented approach is general and can be used with all classification models that output probabilities...
Marko Robnik-Sikonja, Igor Kononenko
GECCO
2007
Springer
184views Optimization» more  GECCO 2007»
15 years 3 months ago
Evolving kernels for support vector machine classification
While support vector machines (SVMs) have shown great promise in supervised classification problems, researchers have had to rely on expert domain knowledge when choosing the SVM&...
Keith Sullivan, Sean Luke
ICDM
2009
IEEE
160views Data Mining» more  ICDM 2009»
15 years 6 months ago
Fast Online Training of Ramp Loss Support Vector Machines
—A fast online algorithm OnlineSVMR for training Ramp-Loss Support Vector Machines (SVMR s) is proposed. It finds the optimal SVMR for t+1 training examples using SVMR built on t...
Zhuang Wang, Slobodan Vucetic
87
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TMI
2002
143views more  TMI 2002»
14 years 11 months ago
A Support Vector Machine Approach for Detection of Microcalcifications
In this paper, we investigate an approach based on support vector machines (SVMs) for detection of microcalcification (MC) clusters in digital mammograms, and propose a successive ...
Issam El-Naqa, Yongyi Yang, Miles N. Wernick, Niko...
ISBI
2002
IEEE
16 years 12 days ago
Support vector machine learning for detection of microcalcifications in mammograms
Microcalcification (MC) clusters in mammograms can be an indicator of breast cancer. In this work we propose for the first time the use of support vector machine (SVM) learning fo...
Issam El-Naqa, Yongyi Yang, Miles N. Wernick, Niko...