An enhanced feature selection and cancer classification for microarray data using relaxed Lasso and support vector machine

• Main Authors: Aina Umairah, Mazlan, Noor Azida, Sahabudin, Muhammad Akmal, Remli, Nor Syahidatul Nadiah, Ismail, Adenuga, Kayode I.
• Format: Book Chapter
• Language: English; English
• Published: Elsevier Science Ltd. 2021
• Subjects: QA75 Electronic computers. Computer science; QA76 Computer software; T Technology (General); TA Engineering (General). Civil engineering (General)
• Online Access: http://umpir.ump.edu.my/id/eprint/42557/1/An%20enhanced%20feature%20selection%20and%20cancer%20classification%20for%20microarray.pdf; http://umpir.ump.edu.my/id/eprint/42557/2/An%20enhanced%20feature%20selection%20and%20cancer%20classification%20for%20microarray%20data%20using%20relaxed%20Lasso%20and%20support%20vector%20machine_ABS.pdf; http://umpir.ump.edu.my/id/eprint/42557/; https://doi.org/10.1016/B978-0-323-89824-9.00016-1; https://doi.org/10.1016/B978-0-323-89824-9.00016-1

Cancer is still the main cause of mortality for both men and women all around the world. In fact, about one in six deaths in the world is due to cancer, making it the most common cause of death globally. Lung and breast cancers had the highest mortality rates in men and women, respectively. Early de...