aonotas/adversarial_text
Code for Adversarial Training Methods for Semi-Supervised Text Classification
This project provides code to apply advanced adversarial training techniques for classifying text, even when you have limited labeled data. It takes in text documents and a small set of labeled examples, along with a larger pool of unlabeled text, to produce a robust text classification model. This is useful for machine learning engineers or researchers who are developing text-based AI solutions.
124 stars. No commits in the last 6 months.
Use this if you need to build highly accurate text classifiers, especially when only a small portion of your training data is hand-labeled.
Not ideal if you are looking for an out-of-the-box solution with a user interface, as this requires familiarity with machine learning frameworks and command-line execution.
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124
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28
Language
Python
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Category
Last pushed
Jul 10, 2018
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