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Modeling Partial Customer Churn: On the Value of First Product-Category Purchase Sequences

MIGUÉIS, V. L.; POEL, D. VAN DEN; CAMANHO, A.S.; … - Faculteit Economie en Bedrijfskunde, Universiteit Gent - 2012

variable length of the sequence. In this study we use logistic regression as the classification technique. A real sample of …

Persistent link: https://www.econbiz.de/10011083107

Predicting Partial Customer Churn Using Markov for Discrimination for Modeling First Purchase Sequences

MIGUÉIS, V. L.; POEL, D. VAN DEN; CAMANHO, A.S.; … - Faculteit Economie en Bedrijfskunde, Universiteit Gent - 2012

is modeled using Markov for discrimination. Two classification techniques are used in the empirical study: logistic …

Persistent link: https://www.econbiz.de/10011083140

Technology Classification with Latent Semantic Indexing

THORLEUCHTER, D.; POEL, D. VAN DEN - Faculteit Economie en Bedrijfskunde, Universiteit Gent - 2012

text classification algorithm. Technologies that occur together in the process of creating an application are grouped in …

Persistent link: https://www.econbiz.de/10011083152

Enhanced Decision Support in Credit Scoring Using Bayesian Binary Quantile Regression

MIGUÉIS, V. L.; BENOIT, D. F.; POEL, D. VAN DEN - Faculteit Economie en Bedrijfskunde, Universiteit Gent - 2012

customers. Many classification methods have been suggested to handle this problem in the literature. This paper proposes a model …

Persistent link: https://www.econbiz.de/10011083168

Ensemble classification based on generalized additive models

BOCK, K. W. DE; COUSSEMENT, K.; POEL, D. VAN DEN - Faculteit Economie en Bedrijfskunde, Universiteit Gent - 2009

alternative ensemble strategies for binary classification using GAMs as base classifiers are proposed: (i) GAMbag based on Bagging …

Persistent link: https://www.econbiz.de/10008487280

Improving Customer Attrition Prediction by Integrating Emotions from Client/Company Interaction Emails and Evaluating Multiple Classifiers.

COUSSEMENT, K.; POEL, D. VAN DEN - Faculteit Economie en Bedrijfskunde, Universiteit Gent - 2008

diversity and (ii) choosing the best performing classification technique. (i) With the upcoming interest in new media (e … behaviour is done. (ii) This study compares three classification techniques – i.e. Logistic Regression, Support Vector Machines …

Persistent link: https://www.econbiz.de/10008457953

Customer Base Analysis: Partial Defection of Behaviorally-Loyal Clients in a Non-Contractual FMCG Retail Setting

BUCKINX, W.; POEL, D. VAN DEN - Faculteit Economie en Bedrijfskunde, Universiteit Gent - 2003

-contractual setting. We build a model in order to predict partial defection by behaviorally-loyal clients using three classification … techniques: Logistic regression, ARD Neural Networks and Random Forests. Classification accuracy (PCC) and area under the …

Persistent link: https://www.econbiz.de/10004982894

Predicting Online Purchasing Behavior

BUCKINX, W.R; POEL, D. VAN DEN - Faculteit Economie en Bedrijfskunde, Universiteit Gent - 2003

This empirical study investigates the contribution of different types of predictors to the purchasing behaviour at an online store. We use logit modelling to predict whether or not a purchase is made during the next visit to the website using both forward and backward variable-selection...

Persistent link: https://www.econbiz.de/10004983029

Customer-Adapted Coupon Targeting Using Feature Selection

BUCKINX, W.; MOONS, E.; POEL, D. VAN DEN; WETS, G. - Faculteit Economie en Bedrijfskunde, Universiteit Gent - 2003

the strategy of retailers and manufacturers concerning their target selection since both parties often end up in a battle …

Persistent link: https://www.econbiz.de/10004983154