English: optimisation, machine learning, parameters, lemmatisation, hyphenation
Afrikaans: lemmatisering, masjienleer, optimering, parameters, woordafbreking
English: Determining the algorithmic parameter combinations that deliver the best performance in applications using machine learning algorithms is a very important part in the development process. Exhaustive searches are slow and computationally expensive, which motivates the investigation of more efficient methods of automatic algorithmic parameter optimisation. Wrapped progressive sampling is one such a method and is utilised in a tool named Paramsearch. An alternative method for determining the sizes of the progressive datasets used in the wrapped progressive sampling procedure is proposed and implemented as PSearch. PSearch and Paramsearch are evaluated and compared to an exhaustive search on the tasks of lemmatisation and hyphenation in Afrikaans. Results indicate that both PSearch and Paramsearch are generally more efficient in terms of execution time and computational resources than an exhaustive search. It is also shown that PSearch delivers more accurate results than Paramsearch on the tasks of lemmatisation and hyphenation in Afrikaans.