[null,null,["最后更新时间 (UTC)：2024-08-13。"],[[["Good feature vectors require features that are clearly named and have obvious meanings to anyone on the project."],["Data should be checked and tested for bad data or outliers like inappropriate values before being used for training."],["Features should be sensible, avoiding \"magic values\" that create discontinuities; instead, use separate boolean features or new discrete values to indicate missing data."],["Continuous features should not have magic values representing the absence of measurement, but rather use separate Boolean features or discrete values."],["Discrete numerical features with missing values should be assigned a new value within the finite set, enabling the model to learn weights for each value including missing features."]]],[]]
