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Importance of Feature Engineering in Machine Learning
Effective feature engineering can often outweigh the choice of model in machine learning. Leveraging user history, item information, and contextual data can have a significant impact on model performance. Additionally, obtaining a representative sample of the action space is crucial due to the stochastic nature of sampling. Bandit learning systems face challenges due to the need for a model of the action space, making it essential to have a comprehensive understanding of the available items for accurate probability estimation.