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Comparing Variable Importance in Prediction of Silence Behaviours Between Random Forest and Conditional Inference Forest Models.

Authors:
Stephen Barrett
Geraldine Gray
Colm McGuinness
Michael Knoll

Keywords: Random Forest; Variable Importance; Bias; PDP; Survey Data; Culture; GLOBE; Organisational Silence.

Abstract:
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.

Pages: 28 to 34

Copyright: Copyright (c) IARIA, 2020

Publication date: October 25, 2020

Published in: conference

ISSN: 2308-4464

ISBN: 978-1-61208-816-7

Location: Nice, France

Dates: from October 25, 2020 to October 29, 2020