我正在尝试使用包含在用户定义指标中的Spearman相关性来查找Scikit-learn中的最近邻居。出于某种原因，它仅在我的训练数据中的列数为5且k = 5时才有效。对于任何其他组合（例如，列数= 8和k = 6），它会给我以下错误。 （此处列车和测试装置有4列，k = 4）。如果我使用Pearson进行相关，它的效果非常好。有谁知道为什么会发生这种情况或如何解决它？谢谢。
from scipy.stats import spearmanr
def spearmancorr(x,y):
rho, pval = spearmanr(x,y, axis=0)
return rho * (-1)
from sklearn.neighbors import NearestNeighbors
nbrs = NearestNeighbors(n_neighbors=4, algorithm='ball_tree', metric=spearmancorr)
nbrs.fit(train)
dist, ind = nbrs.kneighbors(test)
SystemError Traceback (most recent call last)
<ipython-input-11-f04b508b1263> in <module>()
5 for i in range(1):
6 nbrs = NearestNeighbors(n_neighbors=4, algorithm='ball_tree', metric=spearmancorr)
----> 7 nbrs.fit(train)
8 dist, ind = nbrs.kneighbors(test)
9 print "for: " + funcs[i]
C:\Users\AppData\Local\Enthought\Canopy\User\lib\site-packages\sklearn\neighbors\base.pyc in fit(self, X, y)
797 or [n_samples, n_samples] if metric='precomputed'.
798 """
--> 799 return self._fit(X)
C:\Users\AppData\Local\Enthought\Canopy\User\lib\site-packages\sklearn\neighbors\base.pyc in _fit(self, X)
238 self._tree = BallTree(X, self.leaf_size,
239 metric=self.effective_metric_,
--> 240 **self.effective_metric_params_)
241 elif self._fit_method == 'kd_tree':
242 self._tree = KDTree(X, self.leaf_size,
SystemError: NULL result without error in PyObject_Call