2015 · 34 citations · 24 references
ComputingComputer ScienceComputational LinguisticsMachine LearningNatural Language ProcessingActive LearningAnnotationClassificationRepresentation LearningSupport Vector MachinesText MiningActive Learning DesignActive Learning For ClassificationLogistic RegressionMulticlass Support Vector MachinesMultinomial RegressionNaive BayesNaive Bayes Classification
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 nave Bayes, logistic regression, and support vector machines. We additionally present an active learning method tailored specifically for the learning with rationales framework.
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Scikit-learn: Machine Learning in Python
Fabián Pedregosa, Gaël Varoquaux, Alexandre Gramfort et al. · arXiv (Cornell University) · 2012 · 63.7K citations · Full text
Learning Word Vectors for Sentiment Analysis
Andrew L. Maas, Raymond E. Daly, Peter T. Pham et al. · 2011 · 3.3K citations
H. Sebastian Seung, Manfred Opper, Haim Sompolinsky · 1992 · 1.7K citations · Full text