读取前面的训练结果(pickle)，然后对新样本训练，前面的训练结果就没了
能否增量，或者有其他方案可以增量吗？
不太懂其中算法，如果是要各个节点互相计算，这就难办了……
能否增量，或者有其他方案可以增量吗？
不太懂其中算法，如果是要各个节点互相计算，这就难办了……
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This topic created in 2276 days ago, the information mentioned may be changed or developed.
Supplement 1 · Aug 11, 2020
搜了一下
https://scikit-learn.org/stable/tutorial/basic/tutorial.html
Refitting and updating parameters
Hyper-parameters of an estimator can be updated after it has been constructed via the set_params() method. Calling fit() more than once will overwrite what was learned by any previous fit():
overwrite，难怪，看样子要用其他方案……
https://scikit-learn.org/stable/tutorial/basic/tutorial.html
Refitting and updating parameters
Hyper-parameters of an estimator can be updated after it has been constructed via the set_params() method. Calling fit() more than once will overwrite what was learned by any previous fit():
overwrite，难怪，看样子要用其他方案……
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dnn 模型保存 继续训练
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如果样本的特征没变，分布情况没变，等同于又多了点训练数据，那模型是可以继续训练的。
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Rivers7Aug 11, 2020
4
torch 和 tf 这些深度学习库是可以保存参数，下次训练重新 load 模型加入新样本继续训练的
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