K-means algorithm in Ruby
K-means Algorithm in Ruby. Contribute to sungwoncho/k_means_ruby development by creating an account on GitHub.
K-means algorithm in Ruby launched on March 13, 2015 with 5 votes and more than 50% of that year's launches. The site was still online in September 2026, 11 years on.
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A k-means clustering algorithm implementation written in Go2018 · github.com · ▲23k-means clustering algorithm implementation written in Go - muesli/kmeans
Want something better than k-means? Try BanditPAM2023 · github.com · ▲281Want something better than k-means? I'm happy to announce our SOTA k-medoids algorithm from NeurIPS 2020, BanditPAM, is now publicly available! `pip install banditpam` or `install.packages("banditpam")` and you're good to go! k-means is one of the most widely-used algorithms to cluster data. However, it has several limitations: a) it requires the use of L2 distance for efficient clustering, which also b) restricts the data you're clustering to be vectors, and c) doesn't require the means to be datapoints in the dataset. Unlike in k-means, the k-medoids problem requires cluster centers to be…
Program Synthesis for Ruby2022 · github.com · ▲82Program synthesis for Ruby. Contribute to ku-progsys/rbsyn development by creating an account on GitHub.
Algorithm Cookbook in Rust2017 · github.com · ▲320Common data structures and algorithms in Rust. Contribute to EbTech/rust-algorithms development by creating an account on GitHub.
Learn Ruby by Example with Challenges2014 · learneroo.com · ▲48
Design, data-structure, algorithm problems and their solutions2016 · github.com · ▲103Problem Solving. Contribute to sangupta/ps development by creating an account on GitHub.
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