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8 changes: 4 additions & 4 deletions README.md
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- This model was built with **CNN, RNN (LSTM and GRU) and Word Embeddings** on **Tensorflow**.

### Data: [Kaggle San Francisco Crime](https://www.kaggle.com/c/sf-crime/data)
- Input: **Descript**
- Input: **Description**
- Output: **Category**
- Examples:

Descript | Category
Description | Category
-----------|-----------
GRAND THEFT FROM LOCKED AUTO|LARCENY/THEFT
POSSESSION OF NARCOTICS PARAPHERNALIA|DRUG/NARCOTIC
AIDED CASE, MENTAL DISTURBED|NON-CRIMINAL
AGGRAVATED ASSAULT WITH BODILY FORCE|ASSAULT
ATTEMPTED ROBBERY ON THE STREET WITH A GUN|ROBBERY

### Train:
- Command: python3 train.py train_data.file train_parameters.json
- Example: ```python3 train.py ./data/train.csv.zip ./training_config.json```

### Predict:
- Command: python3 predict.py ./trained_results_dir/ new_data.csv
- Example: ```python3 predict.py ./trained_results_1478563595/ ./data/small_samples.csv```

### Reference:
- [Implement a cnn for text classification in tensorflow](http://www.wildml.com/2015/12/implementing-a-cnn-for-text-classification-in-tensorflow/)