Sentense-Classification-with-CNN

Sentence Level Text Classification with Convolutional Neural Networks

Project: Text Classification using Convolutional Neural Network

Details:

• This is a multi-class text classification (sentence classification) problem.
• The goal of this project is to classify Consumer Complaints into classes.
• Also Extract if some Maintenance issue is mentioned in customer reivew.
• The model was built with Convolutional Neural Network (CNN) and Word Embeddings on Tensorflow.

Requirements

• Python 3
• Tensorflow
• Numpy
• Pandas

Data Format:

• Input: consumer_complaint_narrative

• Output: product

Train:

• Command: python3 train.py training_data.file parameters.json
• Example: python3 train.py ./data/consumer_complaints.csv.zip ./parameters.json

A directory will be created during training, and the trained model will be saved in this directory.

Predict:

Provide the model directory (created when running train.py) and new data to predict.py.

• Command: python3 predict.py ./trained_model_directory/ new_data.file
• Example: python3 predict.py ./trained_model_1479757124/ ./data/small_samples.json

References

• Convolutional Neural Networks for Sentence Classification
• A Sensitivity Analysis of (and Practitioners' Guide to) Convolutional Neural Networks for Sentence Classification