Amazon web services sagemaker实时预测中的特征提取

我想使用sagemaker部署一个用于欺诈检测的实时预测机器学习模型

我使用sagemaker jupyter实例：

-load my training data from s3 contains transactions
-preprocessing data and features engineering (i use category_encoders to encode the categorical value)
-training the model and configure the endpoint

对于推断步骤，我使用了一个lambda函数，该函数调用我的端点来获得每个实时事务的预测

should i calculte again all the features for this real time transactions in lambda function ?

for the features when i use category_encoders with fit_transform() function to transform my categorical feature to numerical one, what should I do because the result will not be the same as training set?

is there another method not to redo the calculation of the features in the inference step?

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你对此有更多的见解吗？我也在试着做同样的事情。我听说你可以建立一个“推断管道”，它可以在同一个端点中包括预处理（特征工程）、推断和后处理。这个推断管道也可以从lambda中找到。