Example and Summary of Classifiers with Spam Email Data in R

The increasing volume of unsolicited bulk e-mail (also known as spam) has generated a need for reliable anti-spam filters. Machine learning techniques are frequently employed to automatically filter those spam e-mails quite successfully (to some degree).  The dataset is from the UCI dataset repository https://archive.ics.uci.edu/ml/machine-learning-databases/spambase/) We need to build binary classifiers to classify emails as… Continue reading Example and Summary of Classifiers with Spam Email Data in R

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A SMS Spam Test with Naive Bayes in R, with Text Processing

SMS, or Short Message Service, always contains fraud messages from God-knows-where. With Naive Bayes we can build a classifier to predict the message to be a spam or not, based on NLP(nature language processing). data: http://www.dt.fee.unicamp.br/~tiago/smsspamcollection The above step is EXTREMELY important for MAC users! HAM|SPAM