Search
Code Directory
 ASP
 ASP.NET
 C/C++
 CFML
 CGI/PERL
 Delphi
 Development
 Flash
 HTML
 Java
 JavaScript
 Pascal
 PHP
 Python
 SQL
 Tools
 Visual Basic & VB.NET
 XML
New Code
Vue Injector 3.3
Spectrum Analyzer pro Live 2019
Devart Excel Add-in for HubSpot 2.1
RentALLScript - Airbnb clone 2.2
SuiteCRM Theme Customization 7.11.6
iScripts NetMenus 3.1
iScripts EasyIndex 2.2
iScripts EasySnaps 2.0
Australia MyPost shipping For Magento 2 1.0.0
Australia Post eParcel For Magento 1.1.1
Source Control for SQL Server 2.0
Answers phpSoftPro 3.12
Exlcart 2.0
School College ERP 1.3.2
White-label Grocery Delivery App Solution 2.0
Top Code
iScripts EasySnaps 1
iScripts EasyIndex 1
iScripts NetMenus 2.0
ATN Site Builder 3.0
Azizi search engine script PHP 4.1.10
ATN Resume Finder 2.0
Extreme Injector 3.7
Single Leg MLM 1.2.1
IcrediBB Bulletin Board System 1.0
ICPennyBid Penny Auction Script 4.0
Invoice Manager by PHPJabbers 3.0
A beginner's guide to threading in C#
mp3-manager 1
Jango Clone Script 1.0
Aglowsoft SQL Query Tools 8.2
Top Rated
phpEnter 5.1.
Quick Maps For Dynamics CRM 3.1
Single Leg MLM 1.2.1
Azizi search engine script PHP 4.1.10
Paste phpSoftPro 1.4.1
Extreme Injector 3.7
Deals and Discounts Website Script 1.0.2
Solid File System OS edition 5.1
Classified Ad Lister 1.0
Aglowsoft SQL Query Tools 8.2
Invoice Manager by PHPJabbers 3.0
ICPennyBid Penny Auction Script 4.0
PHP Review Script 1.0
ATN Resume Finder 2.0
ATN Site Builder 3.0
K-medoids 1.0
File ID: 79935






K-medoids 1.0
Download K-medoids 1.0http://www.mathworks.comReport Error Link
License: Shareware
File Size: 20.5 KB
Downloads: 266
User Rating:1 Stars  (1 rating)
Submit Rating:
K-medoids 1.0 Description
Description: Efficient implementation of K-medoids clustering methods. This method is similar to K-means but more robust.
For more detail, please see
http://en.wikipedia.org/wiki/K-medoids

Input data are assumed column vectors.

try
load data;
label=kmedoids(X,3);
scatterd(X,3);

License: Shareware

Related: assumed, Input, Column, Vectors, scatterdx, label dkmedoidsx, Detail, Robust, Clustering

O/S:BSD, Linux, Solaris, Mac OS X

File Size: 20.5 KB

Downloads: 266



More Similar Code

The Affinity Propagation (AP) clustering algorithm
proposed by Frey and Dueck (2007) provides an understandable,
nearly optimal summary of a data set. However,
it suffers two major shortcomings: i) the number of clusters is
vague with the user-defined parameter called self-confidence,
and ii) the quadratic computational complexity. When aiming
at a given number of clusters due to prior knowledge, AP
has to be...



Formatting XML with CSS (a.k.a my favorite jokes) is an article in which author gives details about the procedure for formatting XML documents using Cascading style sheet. For easy understanding the author gives detailed description on formatting...



The Keep It Simple Search (K.I.S.S.) Java applet allows you to query multiple internet search engines in one single step.



Keep It Simple Search (K.I.S.S.) is Java search engine applet allows you to carry out search in a single step over multiple Internet search engines. To use this search, enter a search string and select one or more search engines. The value...



K-Links Directory is a template driven web directory with MySQL backend. This program helps webmasters to earn extra revenue for their online services from advertisers and sponsorships. Site owners would be able to submit their web links to the...



K-Rate is an useful web based PHP script through which the programmers can upload the images just by signing up the membership form. This simple script allows users to chat, submit their blogs and allows to exchage their thoughts. This application...



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.



The kd-tree can be used to organize efficient search for nearest neighbors in a k-dimensional space.



This recipe yields each subset of size k from a super set of size n. I thought I had seen a recipe that did this before, but when I needed it I couldn't find it. There are two methods. The first operates on sets of integers of the form...



Takes a sequence and yields K partitions of it into training and validation test sets. Training sets are of size (k-1)*len(X)/K and partition sets are of size len(X)/K

User Review for K-medoids
- required fields
     

Please enter text on the image