Abstract
The lung cancer is a principle cause of deaths in both women and men. Diagnosis and treatment depend on the cancer type, its stage, and the performance status of status. Depending on the cancer stage, treatments such as chemotherapy, radiotherapy or surgery will be decided. Patient’s survival can be determined based on his overall health, stage and other factors. Only 14 out of 100 people survive around five years after the diagnosis. This paper gives a comparative study of various existing efficient classification models carried out for diagnosing lung cancer and K-Nearest Neighbor classifier outperforms other classifers.
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References
N. Rikhi, Data mining and knowledge discovery in database. Int. J. Eng. Trends Technol. (IJETT) 2(23) (2015)
J. Han, J. Pei, M. Kamber, Data mining: concepts and techniques (Elsevier, Amsterdam, 2011)
N. Singh, S. K. S. Bhadauria, Early detection of cancer using data mining. Int. J. Educ. Manag. Eng. 1(9), 47–52 (2016)
V. Krishnaiah, G .Narsimha, N. Subhash Chandra, Diagnosis of lung cancer prediction system using data mining classification techniques. Int. J. Comput. Sci. Inf. Technol. 1(4), 39–45 (2013)
C.-W. Hsu, C.-J. Lin, Comparison of methods for multiclass support vector machines. IEEE Trans. Neural Netw. 2(13)(2002)
A.K. Yadav, D. Tomar, Clustering of Lung cancer using Foggy K-means, in International Conference on Recent Trends in Information Technology (ICRTIT) (2013), pp. 13–18
R. Bala, D. Kumar, Classification using KNN. Int. J. Comput. Intell. 7(13) (2017)
H.S. Khamis, K.W. Cheruiyot, S. Kimani, Application of k-nearest neighbour classification in medical data mining. Int. J. Inf. Commun. Technol. Res. 4(4) (2014)
T. Christopher, J.J. Banu, Study of classification algorithm for lung cancer prediction. Int. J. Innov. Sci. Eng. Technol. (IIJISET) 2(3) (2016)
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Shetty, R., Geetha, M., Acharya, D.U., Shyamala, G. (2022). A Comparative Study of Efficient Classification Models. In: Shetty D., P., Shetty, S. (eds) Recent Advances in Artificial Intelligence and Data Engineering. Advances in Intelligent Systems and Computing, vol 1386. Springer, Singapore. https://doi.org/10.1007/978-981-16-3342-3_35
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DOI: https://doi.org/10.1007/978-981-16-3342-3_35
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