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A classification algorithm must explore structured, semi-structured or unstructured informational data to detect their similarity and assign them the same category. Among the main applications, we find drilling analysis and data mining. These areas of expertise, which emerged less than a decade ago, are attracting increasing interest from computer scientists, mathematicians and even humanities specialists. The loss of a company's customers, commonly known as "attrition", is a real problem for companies operating in different sectors of activity, especially in competitive situations. It is well…mehr

Produktbeschreibung
A classification algorithm must explore structured, semi-structured or unstructured informational data to detect their similarity and assign them the same category. Among the main applications, we find drilling analysis and data mining. These areas of expertise, which emerged less than a decade ago, are attracting increasing interest from computer scientists, mathematicians and even humanities specialists. The loss of a company's customers, commonly known as "attrition", is a real problem for companies operating in different sectors of activity, especially in competitive situations. It is well known that this phenomenon has not spared the telecommunications sector. To help decision makers to take a decision in front of all these questions, we propose the design of a mini data warehouse (Data marts) to make an easy exploration of the historical data of the customers in connection with the profiles of uses of the customers based on their profiles. In our research we used the DATA MINING method to analyze and predict the data.
Autorenporträt
Ir. Expert en Génie Logiciel, développeur de plusieurs logiciels de Gestion en RDC. Administrateur Gestionnaire et Chargé de Formation du CEISA CONCEPT, Chef de Bureau Chargé de Formation du Ministère de la Jeunesse et Initiation à la Nouvelle Citoyenneté. Assistant à l¿Ex. ISPL / UCCM à kinshasa RDC. Disciple de Professeur Nathanaël Kasoro.