Can We Achieve More with Less? Exploring Data Augmentation for Toxic Comment Classification

2 Jul 2020 Chetanya Rastogi Nikka Mofid Fang-I Hsiao

This paper tackles one of the greatest limitations in Machine Learning: Data Scarcity. Specifically, we explore whether high accuracy classifiers can be built from small datasets, utilizing a combination of data augmentation techniques and machine learning algorithms... (read more)

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Methods used in the Paper

Memory Network
Working Memory Models
Logistic Regression
Generalized Linear Models