Support Vector Machines are models widely used in supervised classification. The classical model minimizes a compromise between the structural risk and empirical risk. In this paper, we consider Machine with feature selection design implement bi-objective evolutionary algorithm for approximating Pareto optimal frontier of two objectives. metaheuristic is based on non-dominated sorting genetic i...

PURPOSE Machine learning is broadly used for clinical data analysis. Before training a model, a machine learning algorithm must be selected. Also, the values of one or more model parameters termed hyper-parameters must be set. Selecting algorithms and hyper-parameter values requires advanced machine learning knowledge and many labor-intensive manual iterations. To lower the bar to machine learn...