Analytical Comparison of Decision Tree and Naive Bayes Classification Methods for Electronic Medical Records
Abstract - A data mining method called classification is used to foretell the group membership of data examples within a given dataset. It is used to divide data into various categories while taking certain restrictions into account. Numerous data mining applications exist for the problem of data classification. This is so that it may be determined how a set of feature variables and an interest-specific target variable relate to one another. As training data associated with class labels are provided as input, classification is seen as an example of supervised learning. Applications for classification algorithms include customer target marketing, medical disease diagnosis, social network analysis, credit card rating, artificial intelligence, and document categorization, among many more. Naive Bayes and Decision Trees are two of the most used types of classification techniques.
Keywords - Classification, Data Mining, Classification Techniques, Naive Bayes, Decision tree, Blood pressure, Age