Research Article
Diabetes Mellitus Disease Prediction Using Machine Learning Classifiers with Oversampling and Feature Augmentation
| Invalue: data (n-dimensional), X1 ϵ R1n1, outvalue (target), Y1 ϵ R1 | | Outvalue: The pp, P1 ϵ [0, 1] of test data (unseen), x1, where | | C1 = 2 (diabetes in (C1) or not (C2)) | (1) | for b1 = 1 to N (n_Bagging) do | (2) | Design a sample (bootstrap) ( from given X1 ϵ , Y1 ϵ R1 | (3) | Design an RF tree using and by recursively repeating. | (4) | The pp P1NRF (x1) where is the prediction of the kth RF. |
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