Active Learning with Rationales for Text Classification

Manali Sharma, Di Zhuang, Mustafa Bilgic

Abstract: We present a simple and yet effective approach that can incorporate rationales elicited from annotators into the training of any offthe-shelf classifier. We show that our simple approach is effective for multinomial na¨ Bayes, logistic regression, and support vector machines. We additionally present an active learning method tailored specifically for the learning with rationales framework.