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## Re: [igraph] : Neighborhood Function

 From: Gábor Csárdi Subject: Re: [igraph] : Neighborhood Function Date: Mon, 13 Jul 2015 18:43:41 -0400

```Hi Patricia,

this is an old email, but if you still need help on this, can you be a
bit more specific about what you want from igraph here? Thanks.

Gabor

On Thu, Jun 25, 2015 at 9:25 AM, patricia <address@hidden> wrote:
> I am currently studying propagation of labels in graphs using
> semi-supervised learning algorithm LGC (Local Global Consistency). The graph
> is generated from a dataset downloaded from the UCI, e.g., Iris, where each
> row is a vertex. I use two algorithms for generating the network, one of
> them is the KNN it receives as a parameter the number of neighbors and the
> value of sigma, the other algorithm used is the E-Cut it receives as
> parameters a real epsilon and the value of sigma . What I want to implement
> is the only formula contained in the file I sent you in section 4.2. That
> average distance will be used as a parameter for network generation methods,
> the value of sigma is what is used in the RBF kernel, and item formula is
> used to estimate its value. To perform the calculation of the distances I
> use a function that calculates the distance between two vertices of the
> graph (or two vectors dataset).
>
> Kernel RBF = exp (-FunctionDistance (xi, xj) / 2 * (sigma) ^ 2)
>
> Estimation of the value of sigma = 1/3 * N * Sum (FunctionDistance (xi,
> xik)) which is precisely the formula I need to implement function using the
> neighborhood (), since the need to know the distance to each vertex xi
> neighbors K closer.
>
>
> Thanks
>
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