Dear Reader, This is the User Manual to run the source code. Remember to reference the codes.
User Manual for Window user (Bayesian)
1. Go to the source directories of Bayesian filtering.
2. Open the workspace.
3. Right click on each project and build it.
4. In Visual Studio, set the project setting with the following arguments for training.
[Directories of ham files] [Directory of spam files] [Parser Type].
5. Then for the classification, the setting for the arguments will be [Directories of the spam message] [directories of the word level probability] [parser type]
User Manual for Window user (SVM)
1. Go to the source directories of SVM.
2. Open the workspace.
3. Right click on each project and build it.
4. For training, set the project setting as the following argument.
[directories of spam files] [directories of ham files].
For training the example, set the project setting as the following argument. [the directories of the trainin.dat] [model.dat]
For classification, set the project setting as the following argument.
[directories of the spam message] [directories of the model.dat] [directories of the Word_count.dat]
User commands for Linux User (Bayesian)
1) Go to the application at the UBUNTU GUI and select terminal.
2) In the terminal, type the command to link to the Bayesian directories.
3) To compile the source code, type make-clean then type make. Now the file is compiled and the binary will be generate in the bin directory.
4) To train the dataset, go to the spamfiltering directories and type ./bin/trainer ../spam_files ../ham_files WORD
5) To classify the spam, type ./bin/classifier
User command for Linux User (SVM)
1. Go to the application at the UBUNTU GUI and select terminal.
2. In the terminal, change the directory to SVM_spam by typing cd Desktop\SVM_spam
3. To compile the source code, type make-clean then type make. Now the file is compiled and the binary will be generate in the bin directory.
4. To run the feature extractor, type ./bin/feature_extractor ../spam_files ../ham_files
5 . To run the svm_learn, type ./bin/svm_learn ../training.dat model.data
6. Then type cat training.dat
1 comments:
Thank you for the info. It sounds pretty user friendly. I guess I’ll pick one up for fun. thank u
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