Abstract
This paper analyzes the DNA sequences of cancer patients using machine learning techniques. Cancer is one of the most prevalent and painful diseases of modern era, in terms of yearly new cases and death rate. Every year, a huge population dies due to this deadly disease. Researchers from different domains are exploring the approaches to counter this disease. In recent years, machine learning has been used for analysis of DNA sequences of cancer patients. The authors of this paper believe that a machine learning solution provides a more elegant and effective solution to the identification of cancer patients. In the same direction, this paper analyzes the DNA sequences of cancer patients using various classification techniques. Based on this study, it can be concluded that cancer disease for people can be diagnosed easily based on their DNA sequences Different classifiers have been used for the analysis purpose such as artificial neural network, k-nearest neighbors. decision trees, fuzzy classifier, Navies Bayes classifier, random forest and support vector machine. Based on the analysis of results, it has been found that these classifiers provide sufficient performance in terms of accuracy, recall, specificity and other parameters. The paper also highlights the best classifier in various scenarios and recommendations have also been provided.