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Biomedical data is filled with continuous real values; these values in the feature set tend to create problems like underfitting, the curse of dimensionality and increase in misclassification rate because of higher variance. In response, pre-processing techniques on dataset minimizes the side effects and have shown success in maintaining the adequate accuracy.

current medical imaging reviews

Multi-objective Evolutionary Approach for the Performance Improvement of Learners using Ensembling Feature Selection and Discretization Technique on Medical Data