Project name: Text_Classifier.

The Basic Idea is that if you give sample text files which are in sub folders where subfolders are the respective category of that file. What This Project aims at doing is make a naive bayes classifier which can predic unclassified text files. The aim is to reach a greated than 85% classification on the given dataset.

Table of Contents:

Description of respective Modules or python files Algorithms used in respective Modules or files Installation: Installation is the next section in an effective README. Tell other users how to install your project locally. Optionally, include a gif to make the process even more clear for other people. Usage: The next section is usage, in which you instruct other people on how to use your project after they’ve installed it. This would also be a good place to include screenshots of your project in action.

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Credits: Research Articles:

License: MIT License

Copyright (c) [2017] [Shivam Chawla]

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.