studentstudent's profile - activity

The implementation of k nearest neighbour in opencv was not professional! In addition, we can not get the indices of the k-nearest neighbours and we can note use an other distance.

In fact I need to use the chi-2 square distance because I have implemented it on mathematica and it gives a good results in my case. I need to use it with opencv knearest neighbours.

So, what is the solution to use other distances than euclidian distance? I think it was a bad idea to use just euclidian distance!! They have to make the distance used as an input parameters!

you can find a long discussion here distance euclidian problems in high dimensions

Hello,

I am using the machine learning k-nearest neighbour algrithm c++. I have a dataset with a high dimensional features. So, the euclidian distance will be not the best. I try to find which distance used in knearest.cpp to change it and used different distances but I could not because the code lacks comments. I find this block in the 189 but It seems that it not used in the find_nearest function. Any help?

> for( ; t < d; t++ )
>                 {
>                 
>                    double t0 = u[t] - v[t];
>                     sum += t0*t0;
>                     
>                 }