Classification of Lung Cancer by Using Machine Learning Algorithms
Joman Al-Tawalbeh, Baraa Alshargawi, Hiam Alquran, Waleed Khalid Al‐Azzawi, Wan Azani Mustafa, Ahmed Alkhayyat
Abstract
Due to the structure of cancer cells, where the majority of the cells are overlapped with each other, early diagnosis of lung cancer is a difficult challenge, so the cause of lung cancer remains unknown and prevention is difficult, early discovery of lung cancer is the only approach to cure it. The classification of lung cancer is a crucial process, based on signs that appear on patients; cancers could easily be predicted and treated. This paper uses KNN, SVM, Naïve Bayes and narrow neural network (NNN) classifiers. KNN showed 85.87% accuracy. SVM, Naïve Bayes and NNN showed 92.6%, 90.3% and 90% accuracy respectively. Results came after the fact that among the four classifiers SVM was the most accurate and much better to classify our data.