AI-based smart prediction of clinical disease using random forest classifier and Naive Bayes

Bayes and Naive Bayes Classifier

Bayes and Naive-Bayes Classifier

Intrusion Detection Using Random Naives Bayes Classifier In Smart Grids

Smart grids (SG) represent succeeding step in modernizing this electrical grid. The communications network is combined with the Smart grid so as to collect data that may be used to increase the potency of the grid, reduce power consumption, and improve the reliability of services, among different varied benefits. Smart Grid communication networks are distinctive in their giant scale. . The Wire...

Pairwise Naive Bayes Classifier

Prediction of Coronary Artery Disease Using Genetic Algorithm Based Feature Selection and Random Forest Classifier

Coronary Artery Disease (CAD) is one of the most prevalent diseases, which can lead to disability and sometimes even death. Diagnostic procedures of CAD are typically invasive, although they do not satisfy the required accuracy. Hence machine learning methods can be used, so that diagnosis can be made faster and with improved accuracy. There are many features that need to be taken into consider...

Improving Naive Bayes Classifier Using Conditional Probabilities

Naive Bayes classifier is the simplest among Bayesian Network classifiers. It has shown to be very efficient on a variety of data classification problems. However, the strong assumption that all features are conditionally independent given the class is often violated on many real world applications. Therefore, improvement of the Naive Bayes classifier by alleviating the feature independence ass...