Search results
44 packages found
turf clusters-kmeans module
Maintenance: 33%. Quality: 43%. Popularity: 17%.
A tool for data PCA(Principle Component Analysis) and cluster(K-Means & K-Medoids).
Maintenance: 30%. Quality: 63%. Popularity: 2%.
k-means based dominant color extraction from images/pixel buffers
Maintenance: 33%. Quality: 56%. Popularity: 1%.
A JS/TS implementation of the k-means algorithm.
Maintenance: 33%. Quality: 51%. Popularity: 2%.
轻量化kd-tree搜索方法
Maintenance: 33%. Quality: 51%. Popularity: 2%.
K-Means to categorize texts using natural algorithm
Maintenance: 30%. Quality: 53%. Popularity: 0%.
Density Based Clustering in JavaScript
Maintenance: None. Quality: 54%. Popularity: 18%.
Configurable k-means & k-medians (with k-means++ initialization) for n-D vectors
Maintenance: 33%. Quality: 44%. Popularity: 2%.
Removes colors from an image file
Maintenance: 28%. Quality: 51%. Popularity: 0%.
Incrementally partition data into `k` clusters.
- stdlib
- stdmath
- stdml
- ml
- machine
- learning
- mathematics
- math
- statistics
- stats
- data mining
- quantization
- lloyds algorithm
- euclidean
- View more
Maintenance: 25%. Quality: 51%. Popularity: 2%.
[demo](https://ppzreboot.github.io/k-colors.js/) | [github](https://github.com/ppzreboot/k-colors.js) | [npm](https://www.npmjs.com/package/k-colors)
Maintenance: 33%. Quality: 41%. Popularity: 1%.
Straightforward fuzzy matching, information retrieval and NLP building blocks for JavaScript.
- bloom filter
- canberra
- caverphone
- chebyshev
- cologne
- cosine
- clustering
- daitch-mokotoff
- dice
- fingerprint
- fuzzy
- hamming
- k-means
- jaccard
- View more
Maintenance: None. Quality: 63%. Popularity: 7%.
Super fast simple k-means and k-means++ clustering for unidimiensional and multidimensional data. Works in node and browser
Maintenance: None. Quality: 41%. Popularity: 18%.
A fast and minimal wasm-compatible color quantization library written in Rust
Maintenance: 33%. Quality: 32%. Popularity: 0%.
A typescript implementation of the k-means algorithm with different customization capabilities.
Maintenance: None. Quality: 63%. Popularity: 1%.
Clustering geoJSON with k-means
Maintenance: None. Quality: 63%. Popularity: 0%.
kmeans
Maintenance: None. Quality: 62%. Popularity: 0%.
Node.js asynchronous implementation of the clustering algorithm k-means
Maintenance: None. Quality: 53%. Popularity: 4%.
Implementation of the k-means algorithm to partition the values into the clusters.
Maintenance: None. Quality: 53%. Popularity: 3%.
k-means clustering in TypeScript
Maintenance: None. Quality: 55%. Popularity: 2%.