Question: What is the purpose of the term 'one-hot encoding' in machine learning?Answer: One-hot encoding is a technique used to represent categorical variables as binary vectors. Each category is represented by a unique binary value, with only one bit set to 1 and the rest set to 0. It is commonly used in machine learning algorithms that cannot work directly with categorical data. |
保存以便复习
收藏此条目、标记为困难题，或将其加入复习集合。
这有帮助吗？ 是 否
用户评价最有帮助的内容：
- Explain the concept of feature engineering.
- What is the purpose of regularization in machine learning?
- Explain the term \'hyperparameter\' in the context of machine learning.
- What is the purpose of the activation function in a neural network?
- Explain the term \'precision\' in the context of classification.