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Related Questions
- What are the common techniques for handling class imbalance in entity categorization tasks, especially when using word embeddings as features?
- How can you leverage the properties of word embeddings, such as vector space properties and semantic similarity, to address class imbalance in entity categorization?
- What are some strategies for oversampling the minority class or undersampling the majority class when using word embeddings in entity categorization tasks?
- Can you discuss the impact of class imbalance on the performance of word embedding-based entity categorization models and how to mitigate its effects?
- How do you handle the challenge of class imbalance when using pre-trained word embeddings, such as Word2Vec or GloVe, in entity categorization tasks?
- What are some techniques for feature engineering that can help alleviate class imbalance issues in entity categorization tasks when using word embeddings?
- Can you provide an example of how to use class weight or sampling techniques to handle class imbalance in a word embedding-based entity categorization task?
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