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» Evaluating learning algorithms and classifiers
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113
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CVPR
2006
IEEE
16 years 6 months ago
Learning Boosted Asymmetric Classifiers for Object Detection
Object detection can be posted as those classification tasks where the rare positive patterns are to be distinguished from the enormous negative patterns. To avoid the danger of m...
Xinwen Hou, Cheng-Lin Liu, Tieniu Tan
BIOCOMP
2007
15 years 5 months ago
Biomarker Discovery Across Annotated and Unannotated Microarray Datasets Using Semi-Supervised Learning
The growing body of DNA microarray data has the potential to advance our understanding of the molecular basis of disease. However annotating microarray datasets with clinically us...
Cole Harris, Noushin Ghaffari
COOPIS
2004
IEEE
15 years 7 months ago
Learning Classifiers from Semantically Heterogeneous Data
Semantically heterogeneous and distributed data sources are quite common in several application domains such as bioinformatics and security informatics. In such a setting, each dat...
Doina Caragea, Jyotishman Pathak, Vasant Honavar
135
Voted
KDD
2002
ACM
147views Data Mining» more  KDD 2002»
16 years 4 months ago
A parallel learning algorithm for text classification
Text classification is the process of classifying documents into predefined categories based on their content. Existing supervised learning algorithms to automatically classify te...
Canasai Kruengkrai, Chuleerat Jaruskulchai
JMLR
2006
135views more  JMLR 2006»
15 years 3 months ago
Statistical Comparisons of Classifiers over Multiple Data Sets
While methods for comparing two learning algorithms on a single data set have been scrutinized for quite some time already, the issue of statistical tests for comparisons of more ...
Janez Demsar