Hussein Mohsen

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Random forests have been used as effective models to tackle a number of classification and regression problems. In this paper, we present a new type of Random Forests (RFs) called Red(uced)-RF that adopts a new voting mechanism called Priority Vote Weighting (PV) and a new dynamic data reduction principle which improve accuracy and execution time compared(More)
Random Forests have been used as effective ensemble models for classification. We present in this paper a new type of Random Forests (RFs) called Red(uced) RF that adopts a new dynamic data reduction principle and a new voting mechanism called Priority Vote Weighting (PV) which improve accuracy, execution time and AUC values compared to Breiman's RF. Red-RF(More)
One goal of a social network, as its name suggests, is to provide human beings with a digital platform where they can build social relationships with a spectrum of people they choose. In this paper, we build a new model that uses Facebook data to measure inter-communication between segregated communities in Lebanon, a country whose diverse yet divided(More)
Background: The modified early warning score (MEWS) is a simple clinical scoring system suitable for bedside application used to predict patients who may undergo a cardiorespiratory arrest event at the onset of admission in the hospital. Materials and Methods: The MEWS is a tool for bedside evaluation based on five physiological parameters. Systolic blood(More)
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