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    NIPS
    2001
    131views Information Technology» more  NIPS 2001»
    Model Based Population Tracking and Automatic Detection of Distribution Changes
    13 years 9 months ago
    Model Based Population Tracking and Automatic Detection of Distribution Changes
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    Probabilistic mixture models are used for a broad range of data analysis tasks such as clustering, classification, predictive modeling, etc. Due to their inherent probabilistic na...
    Igor V. Cadez, Paul S. Bradley
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    BMCBI
    2007
    147views more  BMCBI 2007»
    Statistical analysis and significance testing of serial analysis of gene expression data using a Poisson mixture model
    13 years 8 months ago
    Statistical analysis and significance testing of serial analysis of gene expression data using a Poisson mixture model
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    Background: Serial analysis of gene expression (SAGE) is used to obtain quantitative snapshots of the transcriptome. These profiles are count-based and are assumed to follow a Bin...
    Scott D. Zuyderduyn
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    CSDA
    2007
    264views more  CSDA 2007»
    Model-based methods to identify multiple cluster structures in a data set
    13 years 8 months ago
    Model-based methods to identify multiple cluster structures in a data set
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    Model-based clustering exploits finite mixture models for detecting group in a data set. It provides a sound statistical framework which can address some important issues, such as...
    Giuliano Galimberti, Gabriele Soffritti
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    SIGIR
    2008
    ACM
    192views Information Technology» more  SIGIR 2008»
    Learning to rank with partially-labeled data
    13 years 8 months ago
    Learning to rank with partially-labeled data
    Download  ssli.ee.washington.edu
    Ranking algorithms, whose goal is to appropriately order a set of objects/documents, are an important component of information retrieval systems. Previous work on ranking algorith...
    Kevin Duh, Katrin Kirchhoff
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    BMCBI
    2008
    121views more  BMCBI 2008»
    Stability of gene contributions and identification of outliers in multivariate analysis of microarray data
    13 years 8 months ago
    Stability of gene contributions and identification of outliers in multivariate analysis of microarray data
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    Background: Multivariate ordination methods are powerful tools for the exploration of complex data structures present in microarray data. These methods have several advantages com...
    Florent Baty, Daniel Jaeger, Frank Preiswerk, Mart...
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