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» Hedging predictions in machine learning
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KDD
2004
ACM
166views Data Mining» more  KDD 2004»
16 years 5 months ago
Predicting prostate cancer recurrence via maximizing the concordance index
In order to effectively use machine learning algorithms, e.g., neural networks, for the analysis of survival data, the correct treatment of censored data is crucial. The concordan...
Lian Yan, David Verbel, Olivier Saidi
ML
2010
ACM
135views Machine Learning» more  ML 2010»
14 years 11 months ago
Multi-domain learning by confidence-weighted parameter combination
State-of-the-art statistical NLP systems for a variety of tasks learn from labeled training data that is often domain specific. However, there may be multiple domains or sources o...
Mark Dredze, Alex Kulesza, Koby Crammer
PROCEDIA
2010
140views more  PROCEDIA 2010»
15 years 3 months ago
Jaccard Index based availability prediction in enterprise grids
Enterprise Grid enables sharing and aggregation of a set of computing or storage resources connected by enterprise network, but the availability of the resources in this environme...
Mustafizur Rahman 0003, Md. Rafiul Hassan, Rajkuma...
BMCBI
2007
207views more  BMCBI 2007»
15 years 4 months ago
Discovering biomarkers from gene expression data for predicting cancer subgroups using neural networks and relational fuzzy clus
Background: The four heterogeneous childhood cancers, neuroblastoma, non-Hodgkin lymphoma, rhabdomyosarcoma, and Ewing sarcoma present a similar histology of small round blue cell...
Nikhil R. Pal, Kripamoy Aguan, Animesh Sharma, Shu...
BMCBI
2006
100views more  BMCBI 2006»
15 years 4 months ago
STAR: predicting recombination sites from amino acid sequence
Background: Designing novel proteins with site-directed recombination has enormous prospects. By locating effective recombination sites for swapping sequence parts, the probabilit...
Denis C. Bauer, Mikael Bodén, Ricarda Thier...