A GA with supposedly parallel fitness evaluation tunes an MLP on three disease datasets and reports 99.12%, 94.87%, and 100% accuracy, but the test set is used as the tuning objective.
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Development of a Multiprocessing Interface Genetic Algorithm for Optimising a Multilayer Perceptron for Disease Prediction
A GA with supposedly parallel fitness evaluation tunes an MLP on three disease datasets and reports 99.12%, 94.87%, and 100% accuracy, but the test set is used as the tuning objective.