DOC add parameters types to mutual info score
@@ -592,7 +592,7 @@ def mutual_info_score(labels_true, labels_pred, contingency=None):
labels_true : int array, shape = [n_samples]
A clustering of the data into disjoint subsets.
- labels_pred : array-like of shape (n_samples,)
+ labels_pred : int array-like of shape (n_samples,)
A clustering of the data into disjoint subsets.
contingency : {None, array, sparse matrix}, \
@@ -679,7 +679,7 @@ def adjusted_mutual_info_score(labels_true, labels_pred,
labels_true : int array, shape = [n_samples]
A clustering of the data into disjoint subsets.
- labels_pred : array-like of shape (n_samples,)
+ labels_pred : int array-like of shape (n_samples,)
A clustering of the data into disjoint subsets.
average_method : string, optional (default: 'arithmetic')
@@ -798,7 +798,7 @@ def normalized_mutual_info_score(labels_true, labels_pred,
labels_true : int array, shape = [n_samples]
A clustering of the data into disjoint subsets.
- labels_pred : array-like of shape (n_samples,)
+ labels_pred : int array-like of shape (n_samples,)
A clustering of the data into disjoint subsets.
average_method : string, optional (default: 'arithmetic')
