Sklearn Binning Process - 可以 return 一个间隔吗？
Sklearn Binning Process - It is possible to return a interval?
我正在尝试使用 sklearn.preprocessing 中的 KBinsDiscretizer，但它 return 的整数值为 1,2,..,N（表示间隔）。是否有可能 return 一个正确的间隔 (0.2, 0.5) 或者这还没有实现？
基于文档：https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.KBinsDiscretizer.html:
Attributes: n_bins_ : int array, shape (n_features,):
Number of bins per feature. Bins whose width are too small (i.e., <= 1e-8) are removed with a warning. bin_edges_ : array of arrays,
shape (n_features, ):
The edges of each bin. Contain arrays of varying shapes (n_bins_, ) Ignored features will have empty arrays.
在你的情况下这意味着否定。还有一个提示：
The inverse_transform function converts the binned data into the original feature space. Each value will be equal to the mean of the two bin edges.```
我正在尝试使用 sklearn.preprocessing 中的 KBinsDiscretizer，但它 return 的整数值为 1,2,..,N（表示间隔）。是否有可能 return 一个正确的间隔 (0.2, 0.5) 或者这还没有实现？
基于文档：https://scikit-learn.org/stable/modules/generated/sklearn.preprocessing.KBinsDiscretizer.html:
Attributes: n_bins_ : int array, shape (n_features,):
Number of bins per feature. Bins whose width are too small (i.e., <= 1e-8) are removed with a warning. bin_edges_ : array of arrays,shape (n_features, ):
The edges of each bin. Contain arrays of varying shapes (n_bins_, ) Ignored features will have empty arrays.
在你的情况下这意味着否定。还有一个提示：
The inverse_transform function converts the binned data into the original feature space. Each value will be equal to the mean of the two bin edges.```