Optimizing Neural Networks for Academic Performance Classification Using Feature Selection and Resampling Approach

The features present in large datasets significantly affect the performance of machine learning models. Redundant and irrelevant features will be rejected and cause a decrease in machine learning model performance. This paper proposes HyFeS-ROS-ANN: Hybrid Feature Selection and Resampling combinati...

Ful tanımlama

Kaydedildi:

Detaylı Bibliyografya
Asıl Yazarlar:	Didi Supriyadi, Purwanto Purwanto, Budi Warsito
Materyal Türü:	Artigo
Dil:	Inglês
Baskı/Yayın Bilgisi:	Brno University of Technology 2023-12-01
Seri Bilgileri:	Mendel
Konular:	Feature selection Imbalanced dataset Resampling approach Neural network Academic performance Personality
Online Erişim:	http://www.mendel-journal.org/index.php/mendel/article/view/295
Etiketler:	Etiketle Etiket eklenmemiş, İlk siz ekleyin!

Optimizing Neural Networks for Academic Performance Classification Using Feature Selection and Resampling Approach

Benzer Materyaller