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SPAM-Message-Classification

The purpose of this project is to classify if a SMS is a SPAM or not. The main file of the dataset by this link: https://www.kaggle.com/uciml/sms-spam-collection-dataset?select=spam.csv.The data that i used for this project is a subset of an open source default of SMS Spam Collection dataset, which contains SMS text examples and its corresponding labels (or tags: Spam and Ham). The file contains one message per line. Each line consists of two columns: v1 contains the label (ham or spam) and v2 contains the raw text. Bi-directioanl LSTM model provided the highest accuracy in comparison of other classifiers.

The Classifiers used in this project are

  • Naive Bayes Classifier
  • Decision Tree Classifier
  • KNeighbours Classifier
  • Support Vector Classification
  • Gradient Boosting Classifier
  • Bagging Classifier