1. A method of classifying text messages in a mobile phone, the method comprising: training a support vector machine using a plurality of sample spam text messages and a plurality of sample legitimate text messages in a server computer separate from the mobile phone during a training stage to generate an intermediate support vector machine learning model that includes a threshold value and support vectors; deriving the support vector machine (SVM) learning model from the intermediate support vector machine learning model by storing in the SVM learning model the threshold value but not the support vectors from the intermediate support vector machine learning model, a feature set, and score values comprising weights assigned to features in the feature set; providing the SVM learning model in the mobile phone, extracting features from a text message in the mobile phone to generated extracted features; retrieving from the SVM learning model a corresponding score value for each of the extracted features; adding score values of the extracted features to generate a total score; and comparing the total score to the threshold value to determine whether or not the text message is a spam text message.