Affiliation:
1. Lovely Professional University, Phagwara, Punjab, India
Abstract
In machine learning, Naive Bayes is a popular technique that is used for classification that is based on the conditional probability of attributes belonging to a label, in which the attribute is selected by select attribute operator in rapid miner. In this paper, the split operator has used that divides the dataset into training and testing. Training is used to train the naïve Bayes and testing is used to evaluate the model. The result shows that this simple model generates a good fit for the nursing dataset. Total accuracy achieved using this method is 87.86% which is not bad.