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已发布 : Apr 13, 2021
Not on the current edition
This blip is not on the current edition of the Radar. If it was on one of the last few editions it is likely that it is still relevant. If the blip is older it might no longer be relevant and our assessment might be different today. Unfortunately, we simply don't have the bandwidth to continuously review blips from previous editions of the Radar Understand more
Apr 2021
评估 ? 在了解它将对你的企业产生什么影响的前提下值得探索

众多机器学习方法的核心皆在于从一组训练数据创建一个模型。一旦创建了模型,就可以反复使用它。然而世界并不是静止的,通常模型需要随着新数据的出现而改变。单纯地重新训练模型可能会非常缓慢和昂贵。增量学习解决了这个问题,它使从数据流中增量地学习成为可能,从而更快地对变化做出反应。作为额外的好处,计算和内存需求更低,而且是可预测的。我们在基于River框架的实现中积累了良好的经验,但到目前为止,我们需要在模型更新后增加校验,有时要手动进行。

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