NLP: Classification using a Naive Bayes classifier

Here is possible to find the application of the Naive Bayes approach to a specific problem: the classification of SMS into spam ("an undesired messages, e.g. The supporting code can be found here. The data used for such playground activity is the SMS Spam Collection v. 1, a public set of SMS messages that have been collected for mobile phone spam research where each message has been properly labeled as spam or ham. 'In machine learning and statistics, classification is the problem of identifying to which of a set of categories (sub-populations) a new observation belongs, on the basis of a training set of data containing observations (or instances) whose category membership is known. An example would be assigning a given email into "spam" or "non-spam" classes or assigning a diagnosis to a given patient as described by observed characteristics of the patient (gender, blood pressure, presence or absence of certain symptoms, etc.).