Convolutional neural network sequence classifier with a scikit-learn interface.
Usage example
Predicting IMDB review sentiments.:
from keras.datasets import imdb from keras.preprocessing import sequence from sequence_classifiers import CNNSequenceClassifier maxlen = 400 (x_train, y_train), (x_test, y_test) = imdb.load_data(num_words=5000) x_train = sequence.pad_sequences(x_train, maxlen=maxlen) x_test = sequence.pad_sequences(x_test, maxlen=maxlen) clf = CNNSequenceClassifier(epochs=2) clf.fit(x_train, y_train) print(clf.score(x_test, y_test))
Metadata
Release files for sklearn-sequence-classifiers 0.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| sklearn-sequence-classifiers-0.2.tar.gz | 6.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| sklearn_sequence_classifiers-0.2-py2.py3-none-any.whl | Python 3, Python 2 | none | any | Details |
Total release size: 14.6 kB
Release files / sklearn-sequence-classifiers-0.2.tar.gz
| Download URL | sklearn-sequence-classifiers-0.2.tar.gz |
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| Size | 6.5 kB |
| Tags | Source |
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Release files / sklearn_sequence_classifiers-0.2-py2.py3-none-any.whl
| Download URL | sklearn_sequence_classifiers-0.2-py2.py3-none-any.whl |
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| Size | 8.2 kB |
| Tags | Python 2 Python 3 |
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