Shashank R | Sentiment prediction | Added code for sentiment prediction #172
Conversation
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
…gistic.pkl | Added new code for sentiment prediction of text
ShashankR87
changed the title
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
1 participant
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Sentiment Prediction of text
Author Name: Shashank R
This project can be used to classify a paragraph of text as POSITIVE or NEGATIVE based on the sentiments conveyed by it. The project uses a subset of the Sentiment140 dataset of twitter posts.
TF-IDF vectorization is used to extract features from the text and Logistic Regression is used to make the prediction.
Required Libraries: