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Comparing Variable Importance In Prediction Of Silence Behaviours Between Random Forest And Conditional Inference Forest Models., Stephen Barrett Dr, Geraldine Gray Dr, Colm Mcguinness Dr, Michael Knoll Dr.
Comparing Variable Importance In Prediction Of Silence Behaviours Between Random Forest And Conditional Inference Forest Models., Stephen Barrett Dr, Geraldine Gray Dr, Colm Mcguinness Dr, Michael Knoll Dr.
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This paper explores variable importance metrics of Conditional Inference Trees (CIT) and classical Classification And Regression Trees (CART) based Random Forests. The paper compares both algorithms variable importance rankings and highlights why CIT should be used when dealing with data with different levels of aggregation. The models analysed explored the role of cultural factors at individual and societal level when predicting Organisational Silence behaviours.
Modelling The Reporting Culture Within A Modern Organisation, Ewan Douglas, Samuel Cromie, Maria Chiara Leva, Nora Balfe
Modelling The Reporting Culture Within A Modern Organisation, Ewan Douglas, Samuel Cromie, Maria Chiara Leva, Nora Balfe
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Research shows that there are many factors that can influence the operation of a “Reporting Culture” within organisations, ranging from the attitudes to the workers, to the methodology implemented, to the managerial attitudes within the organisation (Reason, 1998). Understanding and modelling these factors may help develop an optimum reporting system. Historically, research has focused on the concept of “Near Miss Reporting” which is based on the idea of identifying the “bottom” of the safety triangle concept put forward in Heinrich (1941) which suggests that for each accident there are dozens of near misses, and identifying these near misses will hopefully …