如何在scikit-learn中将用户定义的指标用于最近的邻居? [英] How to use a user defined metric for nearest neighbors in scikit-learn?

问题描述

我正在使用scikit-learn 0.18.dev0.我知道在此处之前，已经问过完全相同的问题.我尝试了此处显示的答案，但出现以下错误

I am using scikit-learn 0.18.dev0. I know exactly the same question has been asked before here. I tried the answer presented there, I am getting the following error

>>> def mydist(x, y):
...     return np.sum((x-y)**2)
...
>>> X = np.array([[-1, -1], [-2, -1], [-3, -2], [1, 1], [2, 1], [3,   2]])

>>> nbrs = NearestNeighbors(n_neighbors=4, algorithm='ball_tree',
...            metric='pyfunc', func=mydist)

错误消息 _init_params()获得了意外的关键字参数'func'

该选项似乎已被删除.如何在 sklearn.neighbors 中使用用户定义的矩阵?

It looks like this option has been removed. How can I use a user defined matrix in sklearn.neighbors?

推荐答案

正确的关键字是 metric :

import numpy as np
from sklearn.neighbors import NearestNeighbors

def mydist(x, y):
    return np.sum((x-y)**2)

nn = NearestNeighbors(n_neighbors=4, algorithm='ball_tree', metric=myfunc)

X = np.array([[-1, -1], [-2, -1], [-3, -2], [1, 1], [2, 1], [3,   2]])
nn.fit(X)

开发版本的文档字符串中也提到了这一点: https://github.com/scikit-learn/scikit-learn/blob/86b1ba72771718acbd1e07fbdc5caaf65ae65440/sklearn/neighbors/unsupervised.py#L48

This is also mentioned in the docstring in the development version: https://github.com/scikit-learn/scikit-learn/blob/86b1ba72771718acbd1e07fbdc5caaf65ae65440/sklearn/neighbors/unsupervised.py#L48

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