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What is frequency encoding also known as?
In frequency encoding, what is each category replaced with?
What is the main advantage of frequency encoding?
Which type of variables are best suited for frequency encoding?
What is a limitation of frequency encoding?
When might frequency encoding lead to overfitting?
What is a caution to keep in mind when using frequency encoding with high cardinality features?
Which type of machine learning models often work well with frequency encoding?
How can frequency encoding influence model complexity?
What is a future trend in encoding techniques mentioned in the article?
Why is it important to understand the data and experiment with different encoding methods?
What is a key takeaway regarding the use of frequency encoding in data science?
What is the primary step involved in frequency encoding?
What problem might occur if two categories have the same frequency in frequency encoding?
What is an effective strategy to handle new, unseen categories in frequency encoding?
In the context of frequency encoding, what does ‘high cardinality’ refer to?
How does frequency encoding differ from one-hot encoding in terms of model training efficiency?
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