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        "author": "Antti Ajanki",
        "author_email": "antti.ajanki@iki.fi",
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            "Development Status :: 4 - Beta",
            "Intended Audience :: Developers",
            "Intended Audience :: Science/Research",
            "License :: OSI Approved :: BSD License",
            "Programming Language :: Python",
            "Programming Language :: Python :: 2",
            "Programming Language :: Python :: 2.7",
            "Programming Language :: Python :: 3",
            "Programming Language :: Python :: 3.5",
            "Programming Language :: Python :: 3.6",
            "Topic :: Scientific/Engineering :: Information Analysis",
            "Topic :: Software Development :: Libraries"
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        "description": "Sequence classifiers for scikit-learn\n=====================================\n\nConvolutional neural network sequence classifier with a scikit-learn interface.\n\nUsage example\n-------------\n\nPredicting IMDB review sentiments.::\n\n    from keras.datasets import imdb\n    from keras.preprocessing import sequence\n    from sequence_classifiers import CNNSequenceClassifier\n\n    maxlen = 400\n    (x_train, y_train), (x_test, y_test) = imdb.load_data(num_words=5000)\n    x_train = sequence.pad_sequences(x_train, maxlen=maxlen)\n    x_test = sequence.pad_sequences(x_test, maxlen=maxlen)\n\n    clf = CNNSequenceClassifier(epochs=2)\n    clf.fit(x_train, y_train)\n    print(clf.score(x_test, y_test))\n\n\n",
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        "license": "BSD",
        "maintainer": "",
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        "name": "sklearn-sequence-classifiers",
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        "requires_dist": [
            "Keras",
            "h5py",
            "scikit-learn"
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        "summary": "Sequence classifiers for scikit-learn",
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