Browsing by Subject "Classification"

Now showing items 1-5 of 5

  • Discriminative Gaussian Process Latent Variable Model for Classification 

    Unknown author (2007-03-28)
    Supervised learning is difficult with high dimensional input spacesand very small training sets, but accurate classification may bepossible if the data lie on a low-dimensional manifold. GaussianProcess Latent Variable ...

  • Malaria Prediction using Bayesian and other Machine Learning Techniques 

    Hamisu, Ismail Ahmad (2019-09-12)
    Main purpose of data mining is to extract valuable information from available data. With the enormous amount of data stored in files, databases, and repositories, in the healthcare sector, it’s increasingly important, if ...

  • Permutation Tests for Classification 

    Unknown author (2003-08-28)
    We introduce and explore an approach to estimating statisticalsignificance of classification accuracy, which is particularly usefulin scientific applications of machine learning where highdimensionality of the data and the ...

  • Permutation Tests for Classification 

    Unknown author (2003-08-28)
    We introduce and explore an approach to estimating statistical significance of classification accuracy, which is particularly useful in scientific applications of machine learning where high dimensionality of the data and ...

  • Support Vector Machines: Training and Applications 

    Unknown author (1997-03-01)
    The Support Vector Machine (SVM) is a new and very promising classification technique developed by Vapnik and his group at AT&T Bell Labs. This new learning algorithm can be seen as an alternative training technique ...