Abstract The temporal dimension that is ever more prevalent in data makes the data stream mining (incremental learning) an important field of machine learning. In addition to accurate predictions, explanations of models and examples are a crucial component as they provide insight into model’s decision and lessen its black box nature, thus increasing the user’s trust. Proper visual representation of data is... The temporal dimension that is ever more prevalent in data makes the data stream mining (incremental learning) an important field of machine learning. In addition to accurate predictions, explanations of models and examples are a crucial component as they provide insight into model’s decision and lessen its black box nature, thus increasing the user’s trust. Proper visual representation of data is also very relevant to user’s understanding — visualization is often utilised in machine learning since it shifts the balance between perception and cognition to take fuller advantage of the brain’s abilities. In this paper we review visualisation in incremental setting and devise an improved version of an existing visualisation of explanations of incremental models. We discuss the detection of concept drift in data streams and experiment with a novel detection method that uses the stream of model’s explanations to determine the places of change in the data domain. Read More Read Less

Abstract The e-assessment is a subject that has not ceased to arouse the interest of researchers in any field. Our study focuses on the architecture and modeling of e-assessment platforms and the impact of the multi-agent system on talent measurement. We define a metamodel describing the operating paradigm of this tool. The peculiarity of our application framework lies in the study... The e-assessment is a subject that has not ceased to arouse the interest of researchers in any field. Our study focuses on the architecture and modeling of e-assessment platforms and the impact of the multi-agent system on talent measurement. We define a metamodel describing the operating paradigm of this tool. The peculiarity of our application framework lies in the study of the last four ITEF master classes at Hassan II University. For this study, we used the “Innermetrix” tool, an e-assessment platform ranked number 1 worldwide. The objective of this article is to have real competency mapping by defining a digital student repository associated with a digital study agent able to test and evaluate the soft skills of students in terms of output. The objective is to evaluate the cognitive-behavioral dimensions of students after spending two years in a training that combines a theoretical component and another practice. Read More Read Less

Abstract Information Technology has modernized the approaches of the investigation done by the medical researchers as well as the experts in the clinical practice. Recent medical tools allow recording of massive volumes of patient data, which paves the way to know about the disease thoroughly and it helps for better healthcare measurements. But the medical experts in the clinical practice are unable... Information Technology has modernized the approaches of the investigation done by the medical researchers as well as the experts in the clinical practice. Recent medical tools allow recording of massive volumes of patient data, which paves the way to know about the disease thoroughly and it helps for better healthcare measurements. But the medical experts in the clinical practice are unable to get benefit from the massive volumes of patient data. Thus there is a need for the computer based techniques, which supports the medical experts while making the diagnostic decisions. Thus the decision support system provides an intelligent report about the patient status based on the symptoms, lab reports and patient related information. Such Decision Support system helps to enhance the patient healthcare measures automatic based on knowledge discovery. Thus, this paper developed a software tool to validate the clinical data by implementing Fuzzy Logic method and data visualization methods for estimating the stages of the patient affected by the Alzheimer’s disease. Here SAGE Test and ELISA test reports were used as biomarkers to analyze the stages of the Alzheimer’s disease. Read More Read Less