Lung cancer is the most common cancer that kills many people across the world. Many computer-assisted algorithms are used for the analysis of this cancer. In this research, Random Forest and Support Vector Machine (SVM) algorithms are used to predict Lung Cancer. K-NN Algorithm is used for pre-processing the dataset and then, the existing algorithms such as Random Forest and SVM are applied in the dataset for diagnosing the lung cancer in the patients and a newly proposed algorithm, Optimized RF Algorithm combines the characteristics of Random Forest and SVM is used in this research. When compared with the Random Forest algorithm and Support Vector Machine, the results show that the Optimized RF Algorithm (Optimized-RF) gives better performance than the existing algorithms.

Topics
Machine learning, Support vector machine, Organs
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