Decision Tree approach in Machine Learning for Prediction of Cervical Cancer Stages using WEKA
نویسندگان
چکیده
Around the world cervical cancer or malignancy is the main motivation of cancer or tumor death in ladies. It impacts the cervix in the female regenerative framework which prompts death. The decision tree machine learning approach recognizes the phases of cervical disease. Decision tree arrange the phases of the cervical tumor in progressive basic leadership framework approach which manage the oncologist to take decision on phases of cervical disease, which safes human life. The proposed philosophy utilizes the examination information acquired from http://www.igcs.org and drives the prediction towards the phases of cervical cancer utilizing the tool Weka. Keywords—Cervical Cancer-prediction, Weka, Machine Learning, C5, See5, SIPINA, Decision Tree
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Harnessing the Power of Decision Tree approach in Machine Learning for Cervical Cancer Stage Prediction using See5 and SIPINA
Around the globe Cervical cancer is the biggest reason of cancer deaths in women. It influences the cervix in the female regenerative system which prompts death. The decision tree machine learning approach helps to identify the stages of cervical cancer. Decision tree categorize the stages of the cervical cancer in hierarchical decision making system approach which guide the oncologist to take ...
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