Sentiment Analysis

This project aims to study the sentiment of Indian languages:

Example: haan bhai I will be there don't worry

As we can see the sentence is written in english but is bilingual in nature of speech. This project aims to classify the sentiments of the social media text into +ve, -ve and neutral using ML techniques.

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Models

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1. one feature model
2. three feature model
3. four feature model
4. six featur model

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Algorithms

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1. Count Model

2. K-Nearest Neighbours

3. SVM Models: Linear, kernel

4. Tree Models: DT - Decision Trees, RF - Random Forest, GBDT - Gradient Boosted Dcision trees

5. Naive Bayes model

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Improved Model

Modularized and improved model here: https://github.com/gitvivekgupta/Sentiment-Improved-II