期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2018
卷号：6
期号：3
页码：2341
DOI：10.15680/IJIRCCE.2017.0603103
出版社：S&S Publications
摘要：Cancer is a collection of diseases concerning unusual cell intensification by means of the probable orincrease to supplementary parts of the body (Malignant tumors). Under this scheme, we develop association leadmachine learning technique with amalgamation linear regression and naïve bayes to predict or forecast the anticipationof malignancy. In machine learning and insights of the techniques, under the scheme we will emphasize alternativemethodologies using regression and classification vide variable choice, attributes modeling, property choice or variablesubset determination, is the way toward choosing a subset of pertinent highlights for use in display development ofmalignant tumors where the same can be forecasted or predicted for effective treatments and precautions. Under thescheme we moderate the places of interest utilizing machine learning based harsh set proposition and after that applyneed based approach. We propose need based machine learning technique for governance forecast and prediction ofcancer. At elongated proceeding we apply the linear regression and naïve based classification in categorize manner tocovenant with group the dataset as ordinary or unusual forecast of malignancy.
