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» Active Learning to Maximize Area Under the ROC Curve
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ICIP
2004
IEEE
14 years 9 months ago
Identification of insect damaged wheat kernels using transmittance images
We used transmittance images and different learning algorithms to classify insect damaged and un-damaged wheat kernels. Using the histogram of the pixels of the wheat images as th...
A. Enis Çetin, Tom Pearson, Zehra Cataltepe
GCB
2007
Springer
83views Biometrics» more  GCB 2007»
13 years 11 months ago
Supervised Posteriors for DNA-motif Classification
: Markov models have been proposed for the classification of DNA-motifs using generative approaches for parameter learning. Here, we propose to apply the discriminative paradigm fo...
Jan Grau, Jens Keilwagen, Alexander E. Kel, Ivo Gr...
PRIB
2010
Springer
242views Bioinformatics» more  PRIB 2010»
13 years 6 months ago
Consensus of Ambiguity: Theory and Application of Active Learning for Biomedical Image Analysis
Abstract. Supervised classifiers require manually labeled training samples to classify unlabeled objects. Active Learning (AL) can be used to selectively label only “ambiguous...
Scott Doyle, Anant Madabhushi
SIGKDD
2008
150views more  SIGKDD 2008»
13 years 7 months ago
Learning to improve area-under-FROC for imbalanced medical data classification using an ensemble method
This paper presents our solution for KDD Cup 2008 competition that aims at optimizing the area under ROC for breast cancer detection. We exploited weighted-based classification me...
Hung-Yi Lo, Chun-Min Chang, Tsung-Hsien Chiang, Ch...
JMLR
2010
121views more  JMLR 2010»
13 years 2 months ago
A comparison of AUC estimators in small-sample studies
Reliable estimation of the classification performance of learned predictive models is difficult, when working in the small sample setting. When dealing with biological data it is ...
Antti Airola, Tapio Pahikkala, Willem Waegeman, Be...