XGBTree achieved best performance in most of the evaluation metrics (PrePro—Pre-processing type (B—Balanced (ENUS), O—Original data); VarRem—Variable removal (Y—Yes, N—No)).

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posted on 2022-05-27, 17:24 authored by Tuan Tran, Uyen Le, Yihui Shi

XGBTree achieved best performance in most of the evaluation metrics (PrePro—Pre-processing type (B—Balanced (ENUS), O—Original data); VarRem—Variable removal (Y—Yes, N—No)).

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xgboost tree (<predicting breast cancer patients every year neural network models machine learning models machine learning model machine learning methods least training time ensemble algorithm identified breast cancer using breast cancer prediction breast cancer plays balanced accuracy 3 average balanced accuracy improve predictive performance 93 %, max 5 %, max study also identified f1 score 3 experiment results showed div >< p 100 %), sensitivity handling imbalanced data f1 score experiment showed 100 %),imbalanced data best performance 100 %)xgbtree wide range validation dataset support decision successful treatment study provided small portion saves thousands sampling method sampling approach random forest previous knowledge nuclei majority class important attributes healthcare practitioners healthcare organizations effectively detect early detection driven approach critical role comprehensive comparison cell_shape 83 %.

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