Classification of Benign or Malignant Tumor Using Machine Learning

• Published in: IOP conference series. Materials Science and Engineering 2020-11, Vol.995 (1), p.12028
• Main Authors: Kalaiyarasi, M, Dhanasekar, R, Sakthiya Ram, S, Vaishnavi, P.
• Format: Article
• Language: English
• Subjects: Algorithms; Breast cancer; Classification; Machine learning; Side effects; Signs and symptoms; Support vector machines; Tumor detection; Tumors; Weight loss
• ISSN: 1757-8981; 1757-899X
• DOI: 10.1088/1757-899X/995/1/012028

The abnormal growth of the cell in the human body may leads to tumor. There are almost 100 types of cancer will affect the different parts of the human. The affected human may have symptoms like lump, abnormal bleeding, prolonged cough, weight loss etc. And depends on the part where the tumor formed. Breast cancer is one of the types among the 100 types of cancer and it is most commonly found on the female than the male. Breast cancer is a disease that caused due to the over growth of the cell in the breast area and they started to form lump over the breast. The people who are suffering from the breast cancer will have many emotional side effects and they are supped to undergo lot of pain in their day to day life. The most important problem for the health care people is earlier prediction. So, it can be rectified by employing machine learning algorithms in the prediction stage. In this paper the classification algorithms are used to classify whether the tumor is benign or malignant. The supervised learning algorithms of machine learning such as logistic regression, Support vector machine and K Nearest neighbour algorithm are usually used to analyse the tumour detection. Stacking ensemble method used in order to combine the entire three algorithms is proposed and the performance of algorithm is compared with the logistic regression, Support vector machine and K Nearest neighbour algorithm in order to get an efficient model for the classification.