Titlebook: Discovery Science; 24th International C Carlos Soares,Luis Torgo Conference proceedings 2021 Springer Nature Switzerland AG 2021 applied co

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Predicting Reach to Find Persuadable Customers: Improving Uplift Models for Churn Preventionrevent churn, but targeting the right customers on the basis of their historical profile is a difficult task. Companies usually have recourse to two data-driven approaches: churn prediction and uplift modeling. In churn prediction, customers are selected on the basis of their propensity to churn in

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Shapley-Value Data Valuation for Semi-supervised Learningdo-labeled data. The standard approach is to select instances based on the pseudo-label confidence values that they receive from the prediction models. In this paper we argue that this is an indirect approach w.r.t. the main goal of semi-supervised learning. Instead, we propose a direct approach tha

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A Network Intrusion Detection System for Concept Drifting Network Traffic Datatackers constantly use new attack vectors to avoid being detected, concept drift commonly occurs in the network traffic by degrading the effect of the detection model over time also when deep neural networks are used for intrusion detection. To combat concept drift, we describe a methodology to upda

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