Novel Approach to Find the Effective Supervised Machine Learning Algorithm Using Cancer Data Set

Authors

  • N. Senthil Kumar, Dr. K. Mohan Kumar

Keywords:

Machine Learning Algorithms, Supervised Learning Algorithms, Random Forest algorithm, Logistic Regression algorithm, Decision Tree algorithm, NumPy, Pandas, Seaborn.

Abstract

 In recent years, human diseases are increasing rapidly in various categories. One of the main categories of diseases which cause unexpected death is cancer. Several types of cancer are affecting the various parts of the human body like lung, brain, breast, etc. of which breast cancer is the most severe one among them. In this category women are affected too much and sometimes they face a painful death. The medical industry is worrying in search of an effective solution to predict the disease at an earlier stage to save women from death. Several existing research works predicts using various data analytic methods with the measured cancer data or image data. Yet, the accuracy factor in the prediction of the disease over various features needs to be improved. Accuracy in cancer prediction can be improved by learning, analyzing and extracting the complete information from the dataset. This paper is aimed to find the best machine learning algorithm which is used to implement a model to predict breast cancer.

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Published

2022-01-29