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:

<ROOT><DOC>
<DOCNO> DOCUMENT 1 </DOCNO>
 For <TIME TYPE="DATE:DATE">six years</TIME> , <ENTITY TYPE="PERSON">Shubhanshu A. B. Mishra</ENTITY> has made several programming projects after being inspired by <ENTITY TYPE="PERSON">Linus Torvalds</ENTITY>, a very renowned programmer.
</DOC></ROOT>

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