Prediction of Lung Cancer Using Machine Learning Techniques and their Comparative Analysis

YEAR : 2022

Description

The project attempts to evaluate the discriminative power of several predictors in the study to increase the efficiency of lung cancer detection through their symptoms. A number of classifiers including Support Vector Machine (SVM), Logistic Regression, Decision Tree, k- Nearest Neighbour and Naïve Bayes (NB) are evaluated on a benchmark dataset obtained from Kaggle repository.

ADDITIONAL INFORMATION

System Requirements

Operating System : Windows 7,8,10 (64 bit)
Software : Python
Tools : Anaconda (Jupyter notebook and anaconda prompt)

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