FastSent is one of the solution for Sentiment classification using Recurrent Neural Networks(GRU)
Project description
FastSent is Sentiment Classification python library. It uses Sequential model for Sentiment classfication. FastSent is developed using GRU(Gated Recurrent Unit) model.
Requirement
FastSent support Python 3.6 or newer.
Installation
pip install FastSent
Example
This package is being developed for sentiment classfication using Sequential model GRU(Gated Recurrent Unit).
data = 'Sample.csv'
labels = 'sentiment'
text = 'content'
f = FastSent()
X_train, X_test, y_train, y_test = f.train_test_split(data, labels, text)
trained_model = f.fit_train(X_train, y_train, 500, 50, 7789, 5, 4)
prediction = f.predict(trained_model, X_test, y_train, 4)
where sample
is a training file containing labels and text.
References
DataSet Information
[1] Sample DataSet is being used for research purpose from `*data.world* <https://data.world/crowdflower/sentiment-analysis-in-text>`.
Project details
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