• Swarnalatha Prathipati
• Yada Roshik
• Nandini Shailesh Kadre
• Kolla Abhishek
• Kommera Nikhil Reddy

Lung cancer is the leading cause of cancer-related death in this generation and is expected to remain so for the foreseeable future. If lung cancer signs are identified early, the disease may be treatable. The main factor which causes lung cancer is smoking. Various machine learning algorithms can be used to detect lung cancer. In this study, we are using various machine learning algorithms like logistic regression, support vector machine (SVM), k-Nearest Neighbor (KNN), Random forest, decision tree algorithm to detect what type of cancer low, medium, high i.e., low depicts no cancer, medium depicts benign, high depicts malignant is present across different age groups like Youth, Working Class and Elderly. This study will also focus on how smoking affects various. The classification models will be generated using the training data and the corresponding models will be evaluated using the test data to obtain the accuracy of the models. Finally, we will compare the accuracy rates of each classification model we will implement based on metrics such as F1 score, recall, precision, specificity and arrive at a conclusion.

Machine Learning; Decision Trees; Lung Cancer; Non-Small Cell Lung Cancer (NSCLC);Feature selection; Small Cell Lung Cancer (SCLC); Feature Importance; Data Preprocessing; Bootstrapping

"DETECTION OF LUNG CANCER USING SUPERVISED MACHINE LEARNING ALGORITHMS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 3, page no.g424-g428, March-2023, Available :http://www.jetir.org/papers/JETIR2303663.pdf

"DETECTION OF LUNG CANCER USING SUPERVISED MACHINE LEARNING ALGORITHMS", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 3, page no. ppg424-g428, March-2023, Available at : http://www.jetir.org/papers/JETIR2303663.pdf