scikit-learn 适合剩余时间 [英] scikit-learn fit remaining time

问题描述

有没有办法在拟合模型时估计剩余时间?例如

Is there a way to estimate the remaining time when fitting a model? For example

model = sk.ensemble.RandomForestRegressor(n_estimators=10)
model.fit(x, y)

我有一个相当大的数据集(数百万行)，这将需要一些时间，所以我想知道估计时间，以便我可以做其他事情并在过程完成后返回.

I have a quite large dataset (millions of rows), this is going to take some time so I would like to know estimated time so I can do other thigngs and get back when the process is finished.

对于像随机森林这样的集合，剩余时间的估计应该 [合理地] 容易.

With ensembles like random forest estimation of remaining time should be [reasonably] easy.

推荐答案

尝试 verbose 选项.您可以将其更改为 0(无输出)、1(每个作业的更新)和 2(每个树的更新)，例如

Try verbose option. You can change it from 0 (no output), 1 (update for each job), and 2 (update for each tree), e.g.

model = RandomForestRegressor(n_estimators=100, verbose=2, n_jobs=2).fit(X_train, y_train)

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