[Scikit-learn-general] BIRCH: merge subclusters

Hi, I am doing some experiments with BIRCH. When BIRCH finish, I would like to merge subclusters based on some criteria. I am doing this this by calling "merge_subcluster" method on subcluster that I want to merge with, passing it subcluster object of the second cluster:

Re: [Scikit-learn-general] BIRCH: merge subclusters

he model will automatically > recluster the subclusters after identifying them, as long as you specify > either a number of clusters or a clustering model to the n_clusters > parameter. Can you fit this post-processing into that "final clustering" > framework? > > On 8 Febru

Re: [Scikit-learn-general] BIRCH - Testing datasets

it-learn/pull/5593) > but it is under progress. > > On Mon, Nov 30, 2015 at 3:10 PM, Manoj Kumar < > manojkumarsivaraj...@gmail.com> wrote: > >> Hi, >> >> Can you provide your script for testing? >> >> Thanks ! >> >> >> >>

[Scikit-learn-general] BIRCH - Testing datasets

Hi, I am trying to test BIRCH with the original datasets found here: https://cs.joensuu.fi/sipu/datasets/ (100K points, 100 clusters) The problem is setting the threshold. I need to set it above 10 000 to get decent results. That is very weird because on BIRCH example (

Re: [Scikit-learn-general] BIRCH - global step

Hi, Thank you for your answer. That is actually what I was thinking to do. But it seems that it can perform well even with centers (I had a bug in my code). Using the same example for BIRCH comparison with MiniBatch K-means, where BIRCH produces 158 clusters, I was able to find exact number of

[Scikit-learn-general] BIRCH - global step

Hello, As I was writing before, I am trying to improve BIRCH output quality. The idea is to use BIRCH subclusters to estimate the number of clusters K for K-means, and then run the K-means as global step. So far I implemented K-means to be a global step for BIRCH, with selection of K based on

[Scikit-learn-general] BIRCH algorithm global step

Hi, I would like to change the global step of BIRCH algorithm to be performed using K-means instead of AgglomerativeClustering. Is something like that possible? My goal is to use BIRCH for a streaming data and try to improve output quality. The idea is to use BIRCH subclusters to estimate the

Re: [Scikit-learn-general] BIRCH algorithm global step

the examples gallery and contributions are > welcome! > > On 14 October 2015 at 23:27, Dženan Softić <dzen...@gmail.com> wrote: > >> Hi, >> >> I would like to change the global step of BIRCH algorithm to be performed >> using K-means instead of AgglomerativeCl