© Copyright 2000-2015 Source Code Online. Free Source Code and Scripts Downloads.
Description: Hard and soft k-means implemented simply in python (with numpy). Quick and dirty, tested and works on large (10k+ observations, 2-10 features) real-world data.
Related: data mining, machine learning
|More Similar Code|
The k-means algorithm is widely used in a number applications like speech processing and image compression.
This script implements the algorithm in a simple but general way. It performs four basic steps.
1. Define k arbitrary prototypes from the data samples.
2. Assign each sample to the nearest prototype.
3. Recalculate prototypes as arithmetic means.
4. If a prototype changes, repeat step (2).
Codes for fuzzy k means clustering, including k means with extragrades, Gustafson Kessel algorithm, fuzzy linear discriminant analysis. Performance measure is also calculated.
An implementation of "k-Means Projective Clustering" by P. K. Agarwal and N. H. Mustafa.
This method of clustering is based on finding few subspaces such that each point is close to a subspace.
K-means image segmentation based on histogram to reduce memory usage which is constant for any image size.
This is a tool for K-means clustering. After trying several different ways to program, I got the conclusion that using simple loops to perform distance calculation and comparison is most efficient and accurate because of the JIT acceleration in...
[L, C, D] = FKMEANS(X, k) partitions the vectors in the n-by-p matrix X
into k (or, rarely, fewer) clusters by applying the well known batch
K-means algorithm. Rows of X correspond to points, columns correspond to
KNMCluster is an implementation of the K-means clustering algorithm. It takes inputs k and indata. k is the initial guess of the number of clusters.
indata is the aggregate data that you...
Description DC is simple and effective which can outperform the K-means and AP algorithm.
PBKM is simple and effective which can outperform the K-means algorithm.
This is an implementation of the paper
k-means++: the advantages of careful seeding.
It converges very quickly.
All files and free downloads are copyright of their respective owners. We do not provide any hacked, cracked, illegal, pirated version of scripts, codes, components downloads. All files are downloaded from the publishers website, our file servers or download mirrors. Always Virus check files downloaded from the web specially zip, rar, exe, trial, full versions etc. Download links from rapidshare, depositfiles, megaupload etc not published.