Particle Swarm Optimization Feature Selection for Breast Cancer Recurrence Prediction

Women who have recovered from breast cancer (BC) always fear its recurrence. The fact that they have endured the painstaking treatment makes recurrence their greatest fear. However, with current advancements in technology, early recurrence prediction can help patients receive treatment earlier. The...

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Veröffentlicht in:	IEEE access 2018-01, Vol.6, p.29637-29647
Hauptverfasser:	Sakri, Sapiah Binti, Abdul Rashid, Nuraini Binti, Muhammad Zain, Zuhaira
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Breast cancer Classification algorithms Data mining Data models Decision trees Fear Feature extraction Feature selection K-nearest neighbor Model accuracy naïve Bayes Particle swarm optimization Prediction models Predictive models recurrence REPTree
Online-Zugang:	Volltext
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