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Domain Adapted Word Embeddings for Improved Sentiment Classification

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Table 1: This table shows results from the classi-fication task using sentence embeddings obtainedfrom weighted averaging of word embeddings.Metrics reported are average Precision, F-scoreand AUC and the corresponding standard devi-ations
Table 2 presents results from classifying sentences
Table 3: This table shows results using KCCADA embeddings within a BoW framework. Sincefrom tables 1 and 2 we see that the best perform-ing DA embedding is obtained by KCCA, resultsfor this embedding alone are presented in this ta-ble

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