Benjamin Delespierre
Benjamin Delespierre
Thanks @Ninja-007, I'll give it a look. If you have suggestions for implementation feel free to start a PR
See also https://stackoverflow.com/questions/6645895/calculating-the-percentage-of-variance-measure-for-k-means
From this ticket's scope, calculating the Elbow point is someone else's problem. We're just providing the variance here :wink:
Hey, @LarryBarker thanks for submitting an issue, > I can't tell what is happening behind the scenes. You may use a [callback function](https://github.com/bdelespierre/php-kmeans#watch-the-algorithm-run) to tap into the algorithm execution :+1:...
There is unfortunately very little litterature on the topic so I just assumed this is not what the users wanted. That being said, finding the centroid of a group of...
Yes. I would propose something like: ```php $algo = new Kmeans\Algorithm:(new Kmeans\RandomInitialization()); $result = $algo->clusterize($points, $nbClusters); $serialized = serialize($result); // later... $previousRun = unserialize($serialized); $result = $previousRun->resume($newPoints); ```
I've been thinking about a result object for `Algorithm::clusterize`. What do you think of this API? ```php
It's not implemented in #27. I plan to implement that later
Found [this article](https://abnerrjo.github.io/blog/2016/03/12/multithreaded-k-means-in-java/) about an implementation in Java (see PARALLELIZATION ANALYSIS). May be useful.
> If you're considering multithreading, fibers might be an option too. > > https://php.watch/versions/8.1/fibers Looks amazing :star_struck: