• Statistical classification procedures for analyisng functional data 

      Orsmond, Chane (Stellenbosch : Stellenbosch University, 2016-12)
      ENGLISH SUMMARY : Functional data are obtained through the measurement of one or more variables at a set of discrete evaluation points over a continuum such as time, wavelength or values of a spatial variable. Functional ...
    • The saddle-point method and its application to the hill estimator 

      Buitendag, Sven (Stellenbosch : Stellenbosch University, 2016-12)
      ENGLISH SUMMARY : The saddle-point approximation is a highly accurate approximation of the distribution of a random variable. It was originally derived as an approximation in situations where a parameter takes on large ...
    • L-classifier chains classification and variable selection for multi-label datasets 

      Du Toit, Monika (Stellenbosch : Stellenbosch University, 2016-12)
      ENGLISH SUMMARY : Multi-label classification extends binary and multi-class classification to scenarios where every data case is assigned several labels simultaneously. Applications include labelling images with tags, ...
    • An application of geometric data analysis techniques to South African crime data 

      Gurr, Benjamin William (Stellenbosch : Stellenbosch University, 2016-12)
      ENGLISH SUMMARY : Due to the high levels of violent crime in South Africa, improved methods of analysis are required in order to better scrutinize these statistics. This study diverges from traditional multivariate data ...
    • Advances in random forests with application to classification 

      Pretorius, Arnu (Stellenbosch : Stellenbosch University, 2016-12)
      ENGLISH SUMMARY : Since their introduction, random forests have successfully been employed in a vast array of application areas. Fairly recently, a number of algorithms that adhere to Leo Breiman’s definition of a random ...