https://github.com/napsternxg/deepsequenceclassification

Deep neural network based model for sequence to sequence classification
https://github.com/napsternxg/deepsequenceclassification

deep-neural-networks named-entity-recognition sequence-classification

Last synced: 9 days ago
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Deep neural network based model for sequence to sequence classification

• Host: GitHub
• URL: https://github.com/napsternxg/deepsequenceclassification
• Owner: napsternxg
• License: gpl-2.0
• Created: 2015-12-25T06:03:22.000Z (almost 9 years ago)
• Default Branch: master
• Last Pushed: 2017-11-22T04:19:42.000Z (almost 7 years ago)
• Last Synced: 2024-10-14T07:08:52.025Z (23 days ago)
• Topics: deep-neural-networks, named-entity-recognition, sequence-classification
• Language: Python
• Size: 34.2 KB
• Stars: 77
• Watchers: 9
• Forks: 20
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
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# Deep Sequence Classification

Generic library for training models for deep neural networks for text sequence classification tasks. 

## Usage:

* Create a json file `config.json` (default name) using the template in `config.json.sample` and specify the parameters for your training. 

* Best strategy is to save the training and test files in vector format in advance and then give their paths in `data_vectors` parameter in the file. 

* Train a model:

```

python model.py --config config_multitask.json --verbose 1

```

* Resume training from saved weights:

```

python model.py --config config_multitask.json --verbose 1 --weights output/models/model_multi_brnn_multitask_h2-45.h5 --base_epochs 45

```

## Preprocessing:

* Currently, we support the preprocessing for the following file formats:

```

 DOCUMENT 1 

     For six years , Shubhanshu A. B. Mishra has made several programming projects after being inspired by Linus Torvalds, a very renowned programmer.

```

* Each file can contain multiple `DOCNO`. 

* The dir structure consists of many folders of data split for cross validation. It is as follows:

```

data/

data/CV_files

data/CV_files/1/file1.xml

data/CV_files/1/file2.xml

data/CV_files/1/file3.xml

...

data/CV_files/5/file1.xml

data/CV_files/5/file2.xml

```

## Supports:

* Boundary and Category Detection

* Simple RNN and Bidirectional RNN

* Multi task sequence learning (Boundary + Category trained using same model)

* CNN + BRNN

## Coming Up:

## Use Cases:

* Named Entity Recognition

* POS Tagging

* Dependency Parsing

## Author:

* Shubhanshu Mishra

## Dependencies:

* Theano

* Keras

* BeautifulSoup (with lxml)

* numpy

* lxml (requires libxml2, libxslt and libxml2-dev)

Install theano and keras using the following commands:

```

pip install --user --upgrade --no-deps git+git://github.com/Theano/Theano.git

pip install --user --upgrade --no-deps git+git://github.com/fchollet/keras.git

```