Introduction: The early diagnosis of breast cancer as prevalent cancer among women, is a necessity in the research on cancers since it could simplify the clinical management of other patients. The importance of the classification of breast cancer patients into high- or low-risk groups has led research groups in the biomedical and informatics departments to evaluate and use computer techniques s...

Software risk prediction is the most sensitive and crucial activity of Development Life Cycle (SDLC). It may lead to success or failure a project. The should be predicted earlier make software project successful. A model proposed for requirement risks using dataset machine learning techniques. In addition, comparison made between multiple classifiers that are K-Nearest Neighbour (KNN), Average ...

This short paper estimates the state and local fiscal benefits of the Nurse Family Partnership (NFP) program. NFP provides nurse home visiting services to low-income first-time mothers. In addition to social benefits, NFP provides state and local fiscal benefits by reducing costs of social services, welfare, and crime, and increasing tax receipts due to increased earnings of mothers and former ...

The application of data mining algorithms requires the use of powerful software tools. As the number of available tools continues to grow, the choice of the most suitable tool becomes increasingly difficult. This paper present the basic data mining techniques i.e., naive Bayesian tree, RIpple DOwn Rule, naive Bayes and decision tree algorithm J48 for classifying in medical databases. The goal o...

This paper implements the real-valued negative selection with variable-sized detectors (V-Detectors) for projecting the right decision with respect to crude oil price. The Brent crude oil data is retrieved from US department of energy. Using varying radius values of the V-Detector, comparison in terms of detection rate and false alarm rate, with support vector machine, naïve bayes, multi-layer ...