A simple co-training library built on Keras.
Project description
A simple co-training library built with Keras.
Free software: MIT license
Installation
Before installing simple-co-train, please install one of Keras’ backend engines: TensorFlow, Theano, or CNTK.
pip install simple-co-train
Documentation
Basic usage:
from sctrain import CoTrainer, SelectionStrategy
from sctrain.results import print_results
trainer = CoTrainer(
data_path='imdb.csv', # this can be a directory, e.g. 'data'
x_name='review', # optional, defaults to 'text'
y_name='sentiment', # optional, defaults to 'label'
unlabelled_size=0.9, # optional, what portion of total data should be used as unlabelled
train_size=0.8, # optional, what portion of labelled data should be used as training data
mapping={'negative': 0, 'positive': 1} # optional mapping, y column must be 0 or 1
selection = SelectionStrategy.UNSURE_ONLY # optional, can be CONFIDENT_ONLY or BOTH
)
# run the co-training, this may take a while...
trainer.run()
# print out accuracy, f1 score, precision, recall, and labelled samples at each co-training round
print_results(trainer)
Development
To run the all tests run:
tox
Note, to combine the coverage data from all the tox environments run:
Windows |
set PYTEST_ADDOPTS=--cov-append tox |
|---|---|
Other |
PYTEST_ADDOPTS=--cov-append tox |
Changelog
0.1.0 (2020-05-07)
First release on PyPI.
Project details
Release history Release notifications | RSS feed
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