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Resumo(s)
This thesis extends the outcomes of the year-long Project-Based Learning initiative with NOS, a prominent telecommunications company in Portugal, focusing on optimizing the number of clients that should be flagged for specialized call center teams, to increase
clients’ satisfaction. Two contributions improve model performance by addressing outlier management and applying ensemble techniques, each resulting in substantial improvements from initial solution. The remaining two focus on model explainability, including a deeper
dive into the model’s outcomes and a study on how individuals interpret its explanations. Together, these studies complement the work done in PBL by improving both model performance and interpretability.
Descrição
Palavras-chave
Call centers Time series forecasting Prediction modling Outliers Ensemble learning Explainability
