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PRE-PROCESSING DATA ON MULTICLASS CLASSIFICATION OF ANEMIA AND IRON DEFICIENCY WITH THE XGBOOST METHOD

Anemia and iron deficiency are health problems in Indonesia and globally. In Multiclass Classification, data problems often occur, such as missing data, too many variables, and unbalanced data. Then pre-processing data will be carried out using MissForest imputation, Boruta featuring selection, and...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: Fathu Nurrahman, Hari Wijayanto, Aji Hamim Wigena, Nunung Nurjanah
Format: Artigo
Sprache:Inglês
Veröffentlicht: Universitas Pattimura 2023-06-01
Schriftenreihe:Barekeng
Schlagworte:
anemia
missforest
boruta
smote
xgboost
multiclass classification
Online-Zugang:https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/7740
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