Description

Sms Classification Based on Naive Bayes Classifier and Apriori Algorithm Frequent Item set  SMS classification is detecting spam and ham from the large database using Navie Bayes classifier.  Navie Bayes classifier it classify the all words given in sms.  It increases the overall accuracy of classifying text.  we also using Apriori algorithm for efficiency.  Naive Bayes is one of the simplest probabilistic classifiers which are based on Bayes theorem with strong naive independence assumption.  High frequency words which have been processed.  And calculated by running the association rule mining technique Apriori algorithm.  Apriori is an algorithm for frequent item set mining and association rule learning over transactional databases.  It proceeds by identifying the frequent individual items in the database and extending them to larger and larger item sets as long as those item sets appear sufficiently often in the database.