@@ -26,7 +26,7 @@ def optics(X, min_samples=5, max_eps=np.inf, metric='minkowski',
2626 p = 2 , metric_params = None , maxima_ratio = .75 ,
2727 rejection_ratio = .7 , similarity_threshold = 0.4 ,
2828 significant_min = .003 , min_cluster_size = .005 ,
29- min_maxima_ratio = 0.001 , algorithm = 'ball_tree ' ,
29+ min_maxima_ratio = 0.001 , algorithm = 'auto ' ,
3030 leaf_size = 30 , n_jobs = None ):
3131 """Perform OPTICS clustering from vector array
3232
@@ -133,11 +133,11 @@ def optics(X, min_samples=5, max_eps=np.inf, metric='minkowski',
133133 algorithm : {'auto', 'ball_tree', 'kd_tree', 'brute'}, optional
134134 Algorithm used to compute the nearest neighbors:
135135
136- - 'ball_tree' will use :class:`BallTree` (default)
136+ - 'ball_tree' will use :class:`BallTree`
137137 - 'kd_tree' will use :class:`KDTree`
138138 - 'brute' will use a brute-force search.
139139 - 'auto' will attempt to decide the most appropriate algorithm
140- based on the values passed to :meth:`fit` method.
140+ based on the values passed to :meth:`fit` method. (default)
141141
142142 Note: fitting on sparse input will override the setting of
143143 this parameter, using brute force.
@@ -289,11 +289,11 @@ class OPTICS(BaseEstimator, ClusterMixin):
289289 algorithm : {'auto', 'ball_tree', 'kd_tree', 'brute'}, optional
290290 Algorithm used to compute the nearest neighbors:
291291
292- - 'ball_tree' will use :class:`BallTree` (default)
292+ - 'ball_tree' will use :class:`BallTree`
293293 - 'kd_tree' will use :class:`KDTree`
294294 - 'brute' will use a brute-force search.
295295 - 'auto' will attempt to decide the most appropriate algorithm
296- based on the values passed to :meth:`fit` method.
296+ based on the values passed to :meth:`fit` method. (default)
297297
298298 Note: fitting on sparse input will override the setting of
299299 this parameter, using brute force.
@@ -357,7 +357,7 @@ def __init__(self, min_samples=5, max_eps=np.inf, metric='minkowski',
357357 p = 2 , metric_params = None , maxima_ratio = .75 ,
358358 rejection_ratio = .7 , similarity_threshold = 0.4 ,
359359 significant_min = .003 , min_cluster_size = .005 ,
360- min_maxima_ratio = 0.001 , algorithm = 'ball_tree ' ,
360+ min_maxima_ratio = 0.001 , algorithm = 'auto ' ,
361361 leaf_size = 30 , n_jobs = None ):
362362
363363 self .max_eps = max_eps
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