Browsing Faculty of Natural and Agricultural Sciences by Subject "Pattern recognition"
Now showing items 1-2 of 2
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An empirical investigation of alternative semi-supervised segmentation methodologies
(ASSAf, 2019)Segmentation of data for the purpose of enhancing predictive modelling is a well-established practice in the banking industry. Unsupervised and supervised approaches are the two main types of segmentation and examples of ... -
Kernel bandwidth estimation for non-parametric density estimation: a comparative study
(Pattern recognition association of South Africa (PRASA), 2013)We investigate the performance of conventional bandwidth estimators for non- parametric kernel density estimation on a number of representative pattern-recognition tasks, to gain a better understanding of the behaviour of ...