Fiona Bath-Hextall, Heather Wharrad, Jo Leonardi-Bee
Teaching tools in evidence based practice: evaluation of reusable learning objects (RLOs) for learning about meta-analysis
BMC medical education
recently explainability machine deep learning become important area field research well interest due increasing use artificial intelligence ai methods understanding decisions made models explainability artificial intelligence xai due increasing consciousness among things data mining error elimination learning performance various ai algorithms moreover xai allow decisions made models problems transparent well effective study models glass box group decision tree among others black box group random forest among others proposed understand identification selected types currant powders learning process models carried determine accuracy indicators accuracy precision recall f1score visualized using local interpretable model agnostic explanations limes predict effectiveness identifying specific types blackcurrant powders based texture descriptors entropy contrast correlation dissimilarity homogeneity bagging bagging100 decision tree dt0 random forest rf7gini proved effective models framework currant powder interpretability measures classifier performance terms accuracy precision recall f1score bagging100 respectively reached values approximately 0979 comparison dt0 reached values 0968 0972 0968 0969 rf7gini reached values 0963 0964 0963 0963 models achieved classifier performance measures greater 96 future xai using agnostic models additional important tool help analyze data including food products even online