CLASSIFICATION OF BREAST CANCER ON THE STRENGTH OF POTENTIAL RISK FACTORS WITH BOOSTING MODELS: A PUBLIC HEALTH INFORMATICS APPLICATION

Classification of Breast Cancer on the Strength of Potential Risk Factors with Boosting Models: A Public Health Informatics Application

Aim:The diagnosis of breast cancer can be accomplished using an algorithm or an early detection model of breast cancer risk via determining factors.In the present study, gradient boosting machines (GBM), extreme gradient boosting (XGBoost) and light gradient Burners boosting (LightGBM) models were applied and their performances were compared.Method

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Generating Representative Executions [Extended Abstract]

Analyzing the behaviour of a concurrent program Allulose is made difficult by the number of possible executions.This problem can be alleviated by applying the theory of Mazurkiewicz traces to focus only on the canonical representatives of the equivalence classes of the possible executions of the program.This paper presents a generic framework that

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