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@asiffarhankhan
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Change Log:

  • Implemented nltk for training data
  • removed urllib
  • removed textblob
  • added dynamic URL input
  • changed exception to suit newspaper
  • populated positive headlines in positive_headlines.csv and negative in negative_headlines.csv
  • Program shows news author now
  • If there are any clarifications that is needed to be explained regarding the working. please ask as few changes like use of classifier may not be apparent to everyone.

@asiffarhankhan
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ALSO I have added a file named test. It contains a function that can be used to train the classifier...suppose a user finds the sentiment to be unsatisfying he can re label the news into +ve/-ve so the headline along with the new sentiment gets added to the training data (positive_headline.csv/negative_headline.csv) to improve future results,

Although there are some drawbacks

  • multiple data; if added with same values may reduce accuracy
  • user may spoil the data by adding their biased opinions in data
  • too many 'user added data' in either file may result unbalanced positive/negative training data

Due to these reasons the file is added separately and can be deleted in the next commit if not required

@asiffarhankhan asiffarhankhan added the enhancement New feature or request label Aug 30, 2019
@mandjevant mandjevant merged commit b6f5f41 into Learning-Python-Team:master Sep 1, 2019
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