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» Gene function prediction using labeled and unlabeled data
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SIGMOD
1999
ACM
122views Database» more  SIGMOD 1999»
15 years 4 months ago
BOAT-Optimistic Decision Tree Construction
Classification is an important data mining problem. Given a training database of records, each tagged with a class label, the goal of classification is to build a concise model ...
Johannes Gehrke, Venkatesh Ganti, Raghu Ramakrishn...
AAAI
2006
15 years 1 months ago
Automatically Labeling the Inputs and Outputs of Web Services
Information integration systems combine data from multiple heterogeneous Web services to answer complex user queries, provided a user has semantically modeled the service first. T...
Kristina Lerman, Anon Plangprasopchok, Craig A. Kn...
BMCBI
2010
147views more  BMCBI 2010»
14 years 12 months ago
Indirect two-sided relative ranking: a robust similarity measure for gene expression data
Background: There is a large amount of gene expression data that exists in the public domain. This data has been generated under a variety of experimental conditions. Unfortunatel...
Louis Licamele, Lise Getoor
ICML
2005
IEEE
16 years 19 days ago
Harmonic mixtures: combining mixture models and graph-based methods for inductive and scalable semi-supervised learning
Graph-based methods for semi-supervised learning have recently been shown to be promising for combining labeled and unlabeled data in classification problems. However, inference f...
Xiaojin Zhu, John D. Lafferty
BMCBI
2010
111views more  BMCBI 2010»
14 years 12 months ago
Functional Analysis: Evaluation of Response Intensities - Tailoring ANOVA for Lists of Expression Subsets
Background: Microarray data is frequently used to characterize the expression profile of a whole genome and to compare the characteristics of that genome under several conditions....
Fabrice Berger, Bertrand De Meulder, Anthoula Gaig...