Cervical Cancer Abnormalities Prediction using Decision Tree Approach of Machine Learning

Abstract

Cervical cancer is one of the major causes of women's activities. The slavery of the disease is more for every general population. It disturbs the cervix inside the female design which leads to passage. Wellbeing is significant for each lady to lead a decent family life. Innovations additionally bolster malignant growth screening and forecast in various viewpoints. To recognize the malignant growth the characteristic choice measures and choice trees are valuable. It is utilized to assist the specialists with predicting the disease. The proposed technique utilizes the informational collection procured from Palayam and Mathiravilai, Kanyakumari District and foresees the irregularities utilizing weka instruments.

Keywords: Cervical Cancer prediction; Machine Learning; Weka, Decision Tree; J48, Random Tree.