Samenvatting
In manpower planning mathemathical models, based on estimations of
transition probabilities between groups of employees, are used to predict future staff
compositions. Although the quality of the model depends on the division of the staff
in groups, this classification has been neglected in literature.
The present paper investigates whether decision tree learning can be used as a classi-
fication technique in manpower planning. The paper presents a method for dividing
the population according to the available data in the HR database. The approach will
improve predictions and validity of the model. Another advantage of our developed
method is that it can be automated and implemented in software.
Implementation of the method will make it possible for HR departments in a company
to use the models in practice. The approach will be illustrated on a real life human
resources database using statistical software such as R and WEKA
Originele taal-2 | English |
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Titel | The 16th Conference of the Applied Stochastic Models and Data Analysis International Society |
Pagina's | 863-877 |
Status | Published - 2015 |
Evenement | Applied Stochastic Models and Data Analysis - ASMDA2015 - University of Piraeus, Piraeus, Greece Duur: 30 jun 2015 → 4 jul 2015 |
Conference
Conference | Applied Stochastic Models and Data Analysis - ASMDA2015 |
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Land/Regio | Greece |
Stad | Piraeus |
Periode | 30/06/15 → 4/07/15 |