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您是否需要存储旧数据以在sklearn中修改模型？

[英]Do you need to store your old data to refit a model in sklearn?

原文 2018-07-16 18:53:17 2 1 python/ python-3.x/ machine-learning/ scikit-learn/ data-fitting

I am trying to use sklearn to build an Isolation Forest machine learning program to go through a ton of data. 我正在尝试使用sklearn来构建Isolation Forest机器学习程序来处理大量数据。 I can only store the past 10 days of data, so I was wondering: 我只能存储过去10天的数据，所以我想知道：

When I use the "fit" function on new data that comes in, does it refit the model considering the hyper-parameters from the old data without having had access to that old data anymore ? 当我对传入的新数据使用“拟合”功能时，是否考虑到旧数据中的超参数重新调整了模型， 而无需再访问该旧数据 ？ Or is it completely recreating the model? 还是完全重建了模型？

1 个解决方案

In general, only the estimators implementing the partial_fit method are able to do this. 通常，只有实现partial_fit方法的估计器才能执行此操作。 Unfortunately, IsolationForest is not one of them. 不幸的是， IsolationForest不是其中之一。

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