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» On learning algorithm selection for classification
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169
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Publication
400views
14 years 9 months ago
Partitioning Histopathological Images: An Integrated Framework for Supervised Color-Texture Segmentation and Cell Splitting
For quantitative analysis of histopathological images, such as the lymphoma grading systems, quantification of features is usually carried out on single cells before categorizing...
Hui Kong, Metin Gurcan, and Kamel Belkacem-Boussai...
117
Voted
IAAI
2003
15 years 3 months ago
Searching for Hidden Messages: Automatic Detection of Steganography
Steganography is the field of hiding messages in apparently innocuous media (e.g. images), and steganalysis is the field of detecting these covert messages. Almost all steganalysi...
George Berg, Ian Davidson, Ming-Yuan Duan, Goutam ...
119
Voted
ICML
2006
IEEE
16 years 3 months ago
Efficient lazy elimination for averaged one-dependence estimators
Semi-naive Bayesian classifiers seek to retain the numerous strengths of naive Bayes while reducing error by weakening the attribute independence assumption. Backwards Sequential ...
Fei Zheng, Geoffrey I. Webb
116
Voted
ICML
2005
IEEE
16 years 3 months ago
Large scale genomic sequence SVM classifiers
In genomic sequence analysis tasks like splice site recognition or promoter identification, large amounts of training sequences are available, and indeed needed to achieve suffici...
Bernhard Schölkopf, Gunnar Rätsch, S&oum...
126
Voted
ICML
2000
IEEE
16 years 3 months ago
Duality and Geometry in SVM Classifiers
We develop an intuitive geometric interpretation of the standard support vector machine (SVM) for classification of both linearly separable and inseparable data and provide a rigo...
Kristin P. Bennett, Erin J. Bredensteiner