https://github.com/ashwinpn/text-classification

Text classification using various methods.
https://github.com/ashwinpn/text-classification

Last synced: about 5 hours ago
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Text classification using various methods.

• Host: GitHub
• URL: https://github.com/ashwinpn/text-classification
• Owner: ashwinpn
• Created: 2020-02-26T15:30:02.000Z (over 4 years ago)
• Default Branch: master
• Last Pushed: 2020-03-01T01:35:25.000Z (over 4 years ago)
• Last Synced: 2024-11-15T15:15:45.183Z (about 5 hours ago)
• Language: Jupyter Notebook
• Size: 10.7 KB
• Stars: 2
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Dataset

UCI Machine Learning Repository - Yelp/Amazon/IMDB reviews sentiment labelled dataset.

# Text-Classification

Text classification (Sentiment analysis) using various methods.

The purpose of this project is to assert the superiority of models who take context into account to - that is, to analyze the performance of models which consider the fact that input data might be interdependent too.

# Workflow

- First define baseline models : Naive Bayes and Bag of Words.

- Then, apply deep learning - convolutional neural nets (CNN's).

- Develop a Conditional Random Field (CRF) model for text classification (Sentiment Analysis).

- Toy around with LSTM encodoing - X decoding pairs (X = LSTM - Long Short Term Memory RNN / GRU - Gated Recurent Units).

- See how Skip-Thought Vectors fit into this.