Auflistung nach Schlagwort "guidelines."
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- WorkshopbeitragRecommendations to Handle Health-related Small Imbalanced Data in Machine Learning(Mensch und Computer 2020 - Workshopband, 2020) Rauschenberger, Maria; Baeza-Yates, RicardoWhen discussing interpretable machine learning results, researchers need to compare results and reflect on reliable results, especially for health-related data. The reason is the negative impact of wrong results on a person, such as in missing early screening of dyslexia or wrong prediction of cancer. We present nine criteria that help avoiding over-fitting and biased interpretation of results when having small imbalanced data related to health. We present a use case of early screening of dyslexia with an imbalanced data set using machine learning classification to explain design decisions and discuss issues for further research.
- TextdokumentWeb Surveys. A Brief Guide on Usability and Implementation Issues.(Tagungsband UP05, 2005) Kaczmirek, LarsThe first part of this paper introduces three general recommendations (be userfriendly, be trustworthy, be explicit) which should guide the process of conducting and implementing a web survey. The second part develops the recommendations into a list of guidelines grouped according to the different stages of conducting a web survey.