Main Reference PaperSpam filtering using integrated distribution-based balancing approach and regularized deep neural networks, Applied Intelligence, 2018 [Java/Python/R]
  • A proposed spam filter algorithm is integrated with an N-gram tf.idf feature selection, modified distribution-based balancing algorithm, and a regularized deep multi-layer perceptron. A deep learning architecture learns the complex features from highly non-linear and high-dimensional N-gram spam data. Then, it uses this feature to softmax layer is classified either spam or not spam.

+ Description
  • A proposed spam filter algorithm is integrated with an N-gram tf.idf feature selection, modified distribution-based balancing algorithm, and a regularized deep multi-layer perceptron. A deep learning architecture learns the complex features from highly non-linear and high-dimensional N-gram spam data. Then, it uses this feature to softmax layer is classified either spam or not spam.

  • To detect the incoming message either as spam or not spam.

  • To improve the classification accuracy.

+ Aim & Objectives
  • To detect the incoming message either as spam or not spam.

  • To improve the classification accuracy.

  • To evaluate the performance of the proposed method, this scheme applied high-dimensional imbalanced text categorization problems such as news classification or social network profiling.

+ Contribution
  • To evaluate the performance of the proposed method, this scheme applied high-dimensional imbalanced text categorization problems such as news classification or social network profiling.

  • OS: Ubuntu 12.04 LTS 64bit

  • Language: Java/Python/R

+ Software Tools & Technologies
  • OS: Ubuntu 12.04 LTS 64bit

  • Language: Java/Python/R

  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

+ Project Recommended For
  • M.E / M.Tech/ MS / Ph.D.- Customized according to the client requirements.

  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

+ Order To Delivery
  • No Readymade Projects-project delivery Depending on the complexity of the project and requirements.

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