multi-class-text-classification-cnn-rnn
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jiegzhan
Classify Kaggle San Francisco Crime Description into 39 classes. Build the model with CNN, RNN (GRU and LSTM) and Word Embeddings on Tensorflow.
I want to learn about how the best accuracy of your methods is and the comparisons of all your methods.
Any hint? It will be grateful if you could provide some examples.
I learnt that you used tf 0.9 when you built this project. My tf version is 1.0. There are something different such as the location of rnn_cell.py. I've changed the...
Thanks for your sharing project, and I find the "non-static" in the config. I just find the code like this: with open(trained_dir + 'embeddings.pickle', 'wb') as outfile: pickle.dump(embedding_mat, outfile, pickle.HIGHEST_PROTOCOL)...
I get the following error when trying to train : TypeError: __init__() got an unexpected keyword argument 'syntax' Any idea where this comes from? File "train.py", line 8, in import...
Migration to tensorflow 1 I changed the concat from (1,xxx) to (xxx,1) I changed the tf.nn.rnn_ to tf.contrib.rnn But now I have this error in File "train.py", line 161, in...
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE3 instructions, but these are available on your machine and could speed up CPU computations. W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't...
