KNN Mahalanobis distance error

Hi,

When I use the Mahalanobis metric for KNN I always get the error “Must provide either V or VI for Mahalanobis distance” even when I provide V with metric_params. The same request works with sklearn.neighbors.

from pyod.models.knn import KNN  
from pyod.utils.data import generate_data
from sklearn.neighbors import NearestNeighbors
import numpy as np

contamination = 0.1  
n_train = 200  
n_test = 100 

X_train, y_train, X_test, y_test = generate_data(n_train=n_train, n_test=n_test, contamination=contamination)

#Doesn't work (Must provide either V or VI for Mahalanobis distance)
clf = KNN(algorithm='brute', metric='mahalanobis', metric_params={'V': np.cov(X_train)})
clf.fit(X_train)

#Works
nn = NearestNeighbors(algorithm='brute', metric='mahalanobis', metric_params={'V': np.cov(X_train)})
nn.fit(X_train)

[yzhao062]

Thanks for reporting this. It is due to the problem of passing parameters into KDTree. Specifically, it is caused by the difference between the parameters of NearestNeighbors and KDTree…KDTree has a distinct way of using customized distance metrics.

I will fix it in this next few days and update you here.

[yzhao062]

@lachhebo Yeah I think so. See the example provided here: https://github.com/yzhao062/pyod/blob/development/examples/knn_mahalanobis_example.py