ETD

Archivio digitale delle tesi discusse presso l'Università di Pisa

Tesi etd-06112020-203525


Tipo di tesi
Tesi di laurea magistrale
Autore
KUDASHEVA, AMIDA
URN
etd-06112020-203525
Titolo
Impact of the feature selection via Boruta algorithm on the performance of a churn prediction model in the telecommunications sector
Dipartimento
INFORMATICA
Corso di studi
DATA SCIENCE AND BUSINESS INFORMATICS
Relatori
relatore Rinzivillo, Salvatore
Parole chiave
  • modello di previsione
  • telco
  • churn
  • Boruta
  • feature selection
  • customer churn
  • telecommunications
  • prediction model
Data inizio appello
26/06/2020
Consultabilità
Non consultabile
Data di rilascio
26/06/2090
Riassunto
The goal of the thesis is the evaluation of the impact of the feature selection process on the performance of a customer churn prediction model in the telecommunications sector. The feature selection technique used in the paper is a wrapper algorithm Boruta. Various experiments were performed with changes in the parameter values of the Boruta algorithm and a final set of most important features was selected that was used for the prediction model. The study shows the importance of the process of feature selection and it’s impact on the average lift as a measure of performance of the prediction model.
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