文章基本信息

标题：A Machine Learning based Fine-Tuned and Stacked Model: Predictive Analysis on Cancer Dataset
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作者：Ravi Aavula ; R. Bhramaramba
期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2018
卷号：9
期号：11
DOI：10.14569/IJACSA.2018.091191
出版社：Science and Information Society (SAI)
摘要：The earlier forecast and location of disease cells can be useful in curing the illness in medical applications. Knowledge discovery is having many significant roles in health sector, bioinformatics etc. Plenty of hidden information is available in the datasets present in the various domains like - medical information, textual analysis, image attributes exploration etc. Predictive analytics and modeling encompasses a variety of statistical methodologies from machine learning that can analyze the present along with historical facts to make the predictions about the future events. Breast cancer research already has involved with the good amount of progress in recent decade, but due to advancement in technologies, there is still some possibilities for an improvement. In this paper, the fine-tuned and stacked model procedure is presented which is experimented on standard breast cancer dataset. The obtained results show the improvement over state-of-the-art algorithms with improved performance parameters e.g. disease prediction accuracy, sensitivity and better F1 score etc.
关键词：Machine learning; Cancer prediction; Data mining and Knowledge discovery; Supervised learning; Neural Networks