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@@ -27,12 +27,7 @@ class KBinsDiscretizer(BaseEstimator, TransformerMixin): |
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Parameters |
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---------- |
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n_bins : int or array-like, shape (n_features,) (default=5) |
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The number of bins to produce. The intervals for the bins are |
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determined by the minimum and maximum of the input data. |
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Raises ValueError if ``n_bins < 2``. |
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If ``n_bins`` is an array, and there is an ignored feature at |
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index ``i``, ``n_bins[i]`` will be ignored. |
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The number of bins to produce. Raises ValueError if ``n_bins < 2``. |
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encode : {'onehot', 'onehot-dense', 'ordinal'}, (default='onehot') |
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Method used to encode the transformed result. |
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@@ -62,8 +57,7 @@ class KBinsDiscretizer(BaseEstimator, TransformerMixin): |
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Attributes |
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---------- |
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n_bins_ : int array, shape (n_features,) |
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Number of bins per feature. An ignored feature at index ``i`` |
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will have ``n_bins_[i] == 0``. |
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Number of bins per feature. |
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bin_edges_ : array of arrays, shape (n_features, ) |
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The edges of each bin. Contain arrays of varying shapes ``(n_bins_, )`` |
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