问题
How can I do classification or regression in sklearn if I want to weight each sample differently? Is there a way to do it with a custom loss function? If so, what does that loss function look like in general? Is there an easier way?
回答1:
To weigh individual samples, feed a sample_weight array to the estimator's fit method. This should be a 1-d array of length n_samples (i.e. the same dimension as y in most tasks):
estimator.fit(X, y, sample_weight=some_array)
Not all models support this, check the documentation.
来源：https://stackoverflow.com/questions/17265512/scikit-learn-classification-and-regression-with-weights