@@ -1191,7 +1191,7 @@ Target Types
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:term: `multiclass ` targets, horizontally stacked into an array
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of shape ``(n_samples, n_outputs) ``.
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- XXX : For simplicity, we may not always support string class labels
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+ Note : For simplicity, we may not always support string class labels
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for multiclass multioutput, and integer class labels should be used.
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:mod: `~sklearn.multioutput ` provides estimators which estimate multi-output
@@ -1384,7 +1384,7 @@ Methods
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To clear the model, a new estimator should be constructed, for instance
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with :func: `base.clone `.
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- NOTE : Using ``partial_fit `` after ``fit `` results in undefined behavior.
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+ Note : Using ``partial_fit `` after ``fit `` results in undefined behavior.
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``predict ``
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Makes a prediction for each sample, usually only taking :term: `X ` as
@@ -1613,7 +1613,7 @@ functions or non-estimator constructors.
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for some algorithms, an improper distance metric (one that does not
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obey the triangle inequality, such as Cosine Distance) may be used.
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- XXX: hierarchical clustering uses ``affinity `` with this meaning.
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+ Note: Hierarchical clustering uses ``affinity `` with this meaning.
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We also use *metric * to refer to :term: `evaluation metrics `, but avoid
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using this sense as a parameter name.
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