1 citations · 3 across the 4 of their papers we have counts for
4 papers
Sequence-aware item recommendations for multiply repeated user-item interactions
Juan Pablo Equihua, Maged Ali, Henrik Nordmark +1
Recommender systems are one of the most successful applications of machine learning and data science. They are successful in a wide variety of application domains, including e-comm…
Modelling customer churn for the retail industry in a deep learning based sequential framework
Juan Pablo Equihua, Henrik Nordmark, Maged Ali +1
As retailers around the world increase efforts in developing targeted marketing campaigns for different audiences, predicting accurately which customers are most likely to churn ah…
Optimal trees selection for classification via out-of-bag assessment and sub-bagging
Zardad Khan, Naz Gul, Nosheen Faiz +3
The effect of training data size on machine learning methods has been well investigated over the past two decades. The predictive performance of tree based machine learning methods…
Optimal survival trees ensemble
Naz Gul, Nosheen Faiz, Dan Brawn +3
Recent studies have adopted an approach of selecting accurate and diverse trees based on individual or collective performance within an ensemble for classification and regression p…