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 <[email protected]> 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 > > _______________________________________________ > igraph-help mailing list > [email protected] > https://lists.nongnu.org/mailman/listinfo/igraph-help > _______________________________________________ igraph-help mailing list [email protected] https://lists.nongnu.org/mailman/listinfo/igraph-help
