Document Type

Article

Rights

This item is available under a Creative Commons License for non-commercial use only

Disciplines

Information Science, Business and Management., Organisation Theory

Publication Details

DATA ANALYTICS 2020, The Ninth International Conference on Data Analytics

Available on ThinkMind: http://www.thinkmind.org/index.php?view=article&articleid=data_analytics_2020_2_30_60033

IARIA XPS Press

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.

DOI

https://doi.org/10.21427/9rsv-0479


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