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| data_mining:neural_network:word_embeddings [2018/06/09 16:31] – [Sentiment classification] phreazer | data_mining:neural_network:word_embeddings [2018/06/09 16:40] (current) – [Debiasing word embeddings] phreazer | ||
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| * Extract embedding vector for each word | * Extract embedding vector for each word | ||
| * Feed into RNN with softmax output | * Feed into RNN with softmax output | ||
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| + | ===== Debiasing word embeddings ===== | ||
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| + | Bias in text | ||
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| + | Addressing bias in word embessing: | ||
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| + | - Identify bias direction (e.g. gender) | ||
| + | * $e_{he} - e_{she}$, average them | ||
| + | - Neutralize: For every word that is not definitial (legitimate gender component), project | ||
| + | - Equalize pairs: Only difference should be gender (e.g. grandfather vs. grandmother); | ||
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