On the Feature Selection of Microarray Data for Cancer Detection based on Random Forest Classifier

On the Feature Selection of Microarray Data for Cancer Detection based on Random Forest Classifier

Cancer is a disease that can affect all organs of humans. Based on data from the World Health Organization (WHO) fact sheet in 2018, cancer deaths have reached 9.6 million. One known way to detect cancer that is with Microarray Technique, but the microarray data have large dimensions due to the numb...

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Bibliographic Details
Main Authors: Tita Nurul Nuklianggraita, Adiwijaya Adiwijaya, Annisa Aditsania
Format: Article
Language:Indonesian
Published: LPPM Institut Teknologi Telkom Purwokerto 2020-08-01
Series:Jurnal Infotel
Subjects:
cancer, microarray, minimum redundancy maximum relevance (mrmr), least absolute shrinkage and selection operator (lasso), random forest.
cancer
microarray
minimum redundancy maximum relevance (mrmr)
least absolute shrinkage and selection operator (lasso)
random forest
Online Access:https://ejournal.st3telkom.ac.id/index.php/infotel/article/view/485

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https://ejournal.st3telkom.ac.id/index.php/infotel/article/view/485

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