Weak Supervision for Document Classification

Workflow

Weak Supervision for Document Classification

Last edited:

This workflow defines a fully automated web based application that will label your data using weak supervision. The workflow was designed for business analysts to easily go through documents to be labeled in any number of classes. The user provides euristhics, that is simple labeling functions. Some documents gets labeled, a generative model is applied, and a model can be trained using the a probabilistic input. Gradient Boosted Trees was used after the Weak Label. This workflow is made to be deployed on KNIME WebPortal via KNIME Server.

External resources

KNIME WebPortal - knime.com
Data License: Database Contents License (DbCL) v1.0
Data Source: Kaggle - IMDB Review Dataset
Weak Supervision: A New Programming Paradigm for Machine Learning - Alex Ratner et al - The Stanford AI Lab Blog

Legal

By using or downloading the workflow, you agree to our terms and conditions.