Ndeye Niang

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A method to analyse links between binary attributes in a large sparse data set is proposed. Initially the variables are clustered to obtain homogeneous clusters of attributes. Association rules are then mined in each cluster. A graphical comparison of some rule relevancy indexes is presented. It is used to extract best rules depending on the application(More)
Résumé. Cet article propose une comparaison graphique de certains indices de pertinence pour évaluer l'intérêt des règles d'association. Nous nous sommes appuyés sur une étude existante pour sélectionner quelques indices auxquels nous avons ajouté l'indice de Jaccard et l'indice d'accords désaccords (IAD). Ces deux derniers nous semblent plus adaptés pour(More)
Batch processes are widely used in several industrial sectors, e.g. food and pharmaceutical manufacturing. Process performance is described by variables which are monitored as the batch progresses. Data arising from such processes are usually monitored using control charts based on multiway principal components analysis. In this paper we propose a non(More)
In data mining and machine learning, models come from data and provide insights for understanding data (unsupervised classification) or making prediction (supervised learning) (Giudici, 2003, Hand, 2000). Thus the scientific status of this kind of models is different from the classical view where a model is a simplified representation of reality provided by(More)
Receiver operating characteristic (ROC) curves are very popular for evaluating a diagnostic test or score performances in various decision making applications: medicine, marketing, credit scoring etc. The ROC curve provides a concise graphical representation of the trade off between sensitivity and specificity. We will focus here on supervised(More)