• A comparison of support vector machines and traditional techniques for statistical regression and classification 

      Hechter, Trudie (Stellenbosch : Stellenbosch University, 2004-04)
      ENGLISH ABSTRACT: Since its introduction in Boser et al. (1992), the support vector machine has become a popular tool in a variety of machine learning applications. More recently, the support vector machine has also ...
    • The implementation of noise addition partial least squares 

      Moller, Jurgen Johann (Stellenbosch : University of Stellenbosch, 2009-03)
      When determining the chemical composition of a specimen, traditional laboratory techniques are often both expensive and time consuming. It is therefore preferable to employ more cost effective spectroscopic techniques such ...
    • Non-parametric regression modelling of in situ fCO2 in the Southern Ocean 

      Pretorius, Wesley Byron (Stellenbosch : Stellenbosch University, 2012-12)
      ENGLISH ABSTRACT: The Southern Ocean is a complex system, where the relationship between CO2 concentrations and its drivers varies intra- and inter-annually. Due to the lack of readily available in situ data in the ...
    • Strategies for combining tree-based learners 

      Meyer, Nicholas George (Stellenbosch : Stellenbosch University., 2020-04)
      ENGLISH ABSTRACT: In supervised statistical learning, an ensemble is a predictive model that is the conglomeration of several other predictive models. Ensembles are applicable to both classification and regression problems ...