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seq2class is developed for text classification using LSTM

Project description

seq2class is a one stop solution for text classification. Text classification is made easy via seq2class package using sequential model(LSTM). This package is build by harnesing the capabilities of LSTM(Long short term Memory) model.

Requirement

seq2class support Python 3.6 or newer.

Installation

pip install seq2class

Example

This package is being developed for text classification using sequential model.

data = 'movies.csv'
labels = 'title'
text = 'genres'

s = Sequence2class()
X_train, X_test, y_train, y_test = s.train_test_split(data, labels, text)
trained_model = s.fit_train(X_train, y_train, 500, 50, 7789, 5, 4)
prediction = s.predict(trained_model, X_test, y_train, 4)

where movies.csv is a training file containing text and labels.

References

DataSet information


[1]  movies.csv dataset have been used for research purpose from this `*link* <http://files.grouplens.org/datasets/movielens/ml-latest-small.zip>`.

Project details


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Files for seq2class, version 0.3.0
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