Скачать или смотреть Handling High Cardinality with One-Hot Encoding

@genaiexp High cardinality refers to categorical variables with a large number of unique categories. One-hot encoding these variables can lead to a significant increase in the dimensionality of the dataset, which may impact model performance and increase computational costs. When dealing with high cardinality, it's important to strike a balance between model complexity and performance. Consider alternative strategies such as grouping categories, using target encoding, or dimensionality reduction techniques. Implementing these strategies can help manage the memory and computational demands associated with high cardinality while maintaining the integrity and accuracy of the model.