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  • 1. Lavesson, Niklas
    et al.
    Boeva, Veselka
    Tsiporkova, Elena
    Davidsson, Paul
    Malmö högskola, School of Technology (TS). Malmö högskola, Internet of Things and People (IOTAP).
    A method for evaluation of learning components2014In: Automated Software Engineering: An International Journal, ISSN 0928-8910, E-ISSN 1573-7535, Vol. 21, no 1, p. 41-63Article in journal (Refereed)
    Abstract [en]

    Today, it is common to include machine learning components in software products. These components offer specific functionalities such as image recognition, time series analysis, and forecasting but may not satisfy the non-functional constraints of the software products. It is difficult to identify suitable learning algorithms for a particular task and software product because the non-functional requirements of the product affect algorithm suitability. A particular suitability evaluation may thus require the assessment of multiple criteria to analyse trade-offs between functional and non-functional requirements. For this purpose, we present a method for APPlication-Oriented Validation and Evaluation (APPrOVE). This method comprises four sequential steps that address the stated evaluation problem. The method provides a common ground for different stakeholders and enables a multi-expert and multi-criteria evaluation of machine learning algorithms prior to inclusion in software products. Essentially, the problem addressed in this article concerns how to choose the appropriate machine learning component for a particular software product.

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