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>`.
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