线性回归-火车模型问题 [英] Linear Regression - Train Model Problem

问题描述

您好，我正在使用线性回归和训练模型对几个解释性因素进行回归.我已经使用Edit MetaData模块选择了解释因素作为特征，而预测因素作为列车模型模块中的回归列. 但是，训练后的模型表明它已将回归因子的各种值视为特征.我不知道为什么有人知道发生了什么吗? Thx.

Hi, I am using a linear regression and train model to regress a factor on several explanatory factors. I have selected with the Edit MetaData module the explanatory factors as features and the predicted factor as the regressed column in train model module. However, the trained model indicates that it has treated the various values of a regressed factor as features. I don't know why. Does anyone know what is happening? Thx.

推荐答案

感谢您在这里的反馈.有关训练线性回归模型，请参阅以下文档:

Thanks for your feedback here. For training linear regression model, please refer to following document:

https://docs.microsoft.com/zh-cn/azure/machine-learning/studio-module-reference/machine-learning-initialize-model-regression

https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/machine-learning-initialize-model-regression

此致

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