Return-Path: X-Original-To: apmail-mahout-commits-archive@www.apache.org Delivered-To: apmail-mahout-commits-archive@www.apache.org Received: from mail.apache.org (hermes.apache.org [140.211.11.3]) by minotaur.apache.org (Postfix) with SMTP id 4E48510977 for ; Sun, 16 Mar 2014 08:09:33 +0000 (UTC) Received: (qmail 92578 invoked by uid 500); 16 Mar 2014 08:09:29 -0000 Delivered-To: apmail-mahout-commits-archive@mahout.apache.org Received: (qmail 92296 invoked by uid 500); 16 Mar 2014 08:09:28 -0000 Mailing-List: contact commits-help@mahout.apache.org; run by ezmlm Precedence: bulk List-Help: List-Unsubscribe: List-Post: List-Id: Reply-To: dev@mahout.apache.org Delivered-To: mailing list commits@mahout.apache.org Received: (qmail 92277 invoked by uid 99); 16 Mar 2014 08:09:19 -0000 Received: from athena.apache.org (HELO athena.apache.org) (140.211.11.136) by apache.org (qpsmtpd/0.29) with ESMTP; Sun, 16 Mar 2014 08:09:19 +0000 X-ASF-Spam-Status: No, hits=-2000.0 required=5.0 tests=ALL_TRUSTED X-Spam-Check-By: apache.org Received: from [140.211.11.4] (HELO eris.apache.org) (140.211.11.4) by apache.org (qpsmtpd/0.29) with ESMTP; Sun, 16 Mar 2014 08:09:18 +0000 Received: from eris.apache.org (localhost [127.0.0.1]) by eris.apache.org (Postfix) with ESMTP id 30E7723888D7 for ; Sun, 16 Mar 2014 08:08:58 +0000 (UTC) Content-Type: text/plain; charset="utf-8" MIME-Version: 1.0 Content-Transfer-Encoding: 7bit Subject: svn commit: r901786 - in /websites/staging/mahout/trunk/content: ./ users/clustering/visualizing-sample-clusters.html Date: Sun, 16 Mar 2014 08:08:58 -0000 To: commits@mahout.apache.org From: buildbot@apache.org X-Mailer: svnmailer-1.0.9 Message-Id: <20140316080858.30E7723888D7@eris.apache.org> X-Virus-Checked: Checked by ClamAV on apache.org Author: buildbot Date: Sun Mar 16 08:08:57 2014 New Revision: 901786 Log: Staging update by buildbot for mahout Modified: websites/staging/mahout/trunk/content/ (props changed) websites/staging/mahout/trunk/content/users/clustering/visualizing-sample-clusters.html Propchange: websites/staging/mahout/trunk/content/ ------------------------------------------------------------------------------ --- cms:source-revision (original) +++ cms:source-revision Sun Mar 16 08:08:57 2014 @@ -1 +1 @@ -1577980 +1577992 Modified: websites/staging/mahout/trunk/content/users/clustering/visualizing-sample-clusters.html ============================================================================== --- websites/staging/mahout/trunk/content/users/clustering/visualizing-sample-clusters.html (original) +++ websites/staging/mahout/trunk/content/users/clustering/visualizing-sample-clusters.html Sun Mar 16 08:08:57 2014 @@ -205,71 +205,43 @@

Introduction

Mahout provides examples to visualize sample clusters that gets created by -various clustering algorithms like - Canopy Clustering - Dirichlet Process - KMeans - Fuzzy KMeans - MeanShift Canopy - Spectral KMeans -* MinHash

Note

These are Swing programs. You have to be in a window system on the same -machine you run these, or logged in via a "remote desktop" or VNC program.

+our clustering algorithms. Note that the visualization is done by Swing programs. You have to be in a window system on the same +machine you run these, or logged in via a remote desktop.

Pre - Prep

For visualizing the clusters, you would just have to execute the Java -classes under org.apache.mahout.clustering.display package in -mahout-examples module. If you are using eclipse, setup mahout-examples as -a project as specified in Working with Maven in Eclipse -.

For visualizing the clusters, you have to execute the Java +classes under org.apache.mahout.clustering.display package in +mahout-examples module. The easiest way to achieve this is to setup Mahout in your IDE.

Visualizing clusters

The following classes in org.apache.mahout.clustering.display can be run +

The following classes in org.apache.mahout.clustering.display can be run without parameters to generate a sample data set and run the reference -clustering implementations over them: -1. DisplayClustering - generates 1000 samples from three, symmetric +clustering implementations over them:

DisplayClustering - generates 1000 samples from three, symmetric distributions. This is the same data set that is used by the following clustering programs. It displays the points on a screen and superimposes the model parameters that were used to generate the points. You can edit -the generateSamples() method to change the sample points used by these -programs. -1. DisplayClustering - displays initial areas of generated points -1. DisplayDirichlet - uses Dirichlet Process clustering -1. DisplayCanopy - uses Canopy clustering -1. DisplayKMeans - uses k-Means clustering -1. DisplayFuzzyKMeans - uses Fuzzy k-Means clustering -1. DisplayMeanShift - uses MeanShift clustering -1. DisplaySpectralKMeans - uses Spectral KMeans via map-reduce algorithm
-
If you are using Eclipse and have set it up as specified in Pre-Prep, just -right-click on each of the classes mentioned above and choose "Run As - -Java Application". To run these directly from the command line:
+the generateSamples() method to change the sample points used by these +programs.
DisplayClustering - displays initial areas of generated points
DisplayCanopy - uses Canopy clustering
DisplayKMeans - uses k-Means clustering
DisplayFuzzyKMeans - uses Fuzzy k-Means clustering
DisplaySpectralKMeans - uses Spectral KMeans via map-reduce algorithm

If you are using Eclipse, just right-click on each of the classes mentioned above and choose "Run As -Java Application". To run these directly from the command line:

cd $MAHOUT_HOME/examples
-mvn -q exec:java
+mvn -q exec:java -Dexec.mainClass=org.apache.mahout.clustering.display.DisplayClustering

-Dexec.mainClass=org.apache.mahout.clustering.display.DisplayClustering - # substitute other names above for DisplayClustering - # Note: the DisplaySpectralKMeans program does a Hadoop job that takes 3 -minutes on a laptop. Set this MVN_OPTS=300m to give the program enough -memory. You may find that some of the other programs also need more memory.

Note: -* Some of these programs display the sample points and then superimpose all -of the clusters from each iteration. The last iteration's clusters are in +

You can substitute other names above for DisplayClustering.

Note that some of these programs display the sample points and then superimpose all of the clusters from each iteration. The last iteration's clusters are in bold red and the previous several are colored (orange, yellow, green, blue, magenta) in order after which all earlier clusters are in light grey. This helps to visualize how the clusters converge upon a solution over multiple iterations.

By changing the parameter values (k, ALPHA_0, numIterations) and the -display SIGNIFICANCE you can obtain different results.

Screen Capture Animation

See Sample Clusters Animation - for a screen caps of all the above programs, and an animated gif.