%0 Journal Article
%A Smith, Matthew
%A Álvarez González, Francisco
%T A machine learning research template for binary classification problems and shapley values integration
%D 2021
%@ 2665-9638
%U https://hdl.handle.net/20.500.14352/6773
%X This paper documents published code which can help facilitate researchers with binary classification problems and interpret the results from a number of Machine Learning models. The original paper was published in Expert Systems with Applications and this paper documents the code and work-flow with a special interest being paid to Shapley values as a means to interpret Machine Learning predictions. The Machine Learning models used are, Naive Bayes, Logistic Regression, Random Forest, adaBoost, Classification Tree, Light GBM and XGBoost.
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