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sklearn.neighbors.KNeighborsClassifier()函数用于实现k近邻投票算法的分类器。
class sklearn.neighbors.KNeighborsClassifier(n_neighbors=5, weights=’uniform’,
algorithm=’auto’, leaf_size=30,
p=2, metric=’minkowski’,
metric_params=None,
n_jobs=None, **kwargs)
参数:
n_neighbors
: int,optional(default = 5)weights
: str或callable,可选(默认=‘uniform’)algorithm
: {‘auto’,‘ball_tree’,‘kd_tree’,‘brute’},可选leaf_size
: int,optional(默认值= 30)p
: 整数,可选(默认= 2)metric
: 字符串或可调用,默认为’minkowski’metric_params
: dict,optional(默认=None)n_jobs
: int或None,可选(默认=None)警告: 关于最近邻居算法,如果发现两个邻居,邻居k+1和k具有相同距离但不同标签,则结果将取决于训练数据的排序。
例:
>>> X = [[0], [1], [2], [3]]
>>> y = [0, 0, 1, 1]
>>> from sklearn.neighbors import KNeighborsClassifier
>>> neigh = KNeighborsClassifier(n_neighbors=3)
>>> neigh.fit(X, y)
KNeighborsClassifier(...)
>>> print(neigh.predict([[1.1]]))
[0]
>>> print(neigh.predict_proba([[0.9]]))
[[0.66666667 0.33333333]]
https://blog.csdn.net/TeFuirnever/article/details/99818078
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