[GRASS-SVN] r67183 - grass-addons/grass7/vector/v.mrmr

[svn_grass at osgeo.org]

Author: spawley
Date: 2015-12-16 10:35:43 -0800 (Wed, 16 Dec 2015)
New Revision: 67183

Modified:
   grass-addons/grass7/vector/v.mrmr/v.mrmr.html
Log:
Minor update to help file

Modified: grass-addons/grass7/vector/v.mrmr/v.mrmr.html
===================================================================
--- grass-addons/grass7/vector/v.mrmr/v.mrmr.html	2015-12-16 17:38:32 UTC (rev 67182)
+++ grass-addons/grass7/vector/v.mrmr/v.mrmr.html	2015-12-16 18:35:43 UTC (rev 67183)
@@ -8,22 +8,24 @@
 
 <h2>NOTES</h2>
 
-<p>The command line tool needs to be installed separately in a
-location that is recognized by the system or in the PATH. The command
-line tool can be installed on windows (binaries available), linux and OS
-X (needs compilation). Installation instructions are provided on <a
+<p>The command line tool needs to be installed separately in a location
+that is recognized by the system or in the PATH. The command line tool
+can be installed on windows (binaries available), linux and OS X (needs
+compilation). Installation instructions are provided on <a
 href="http://penglab.janelia.org/proj/mRMR/">Peng's Website</a>.
 
 <p>The module requires data within a vector attribute table to be
 arranged in a specific order. The classification variable (i.e., class
 labels) need to be in the first column, except for the cat attribute
 which is not exported. The class label also needs to be in numerical
-form, i.e., 1, 2, 3.... rather than 'forest' or 'urban'.
-	
-<p>The algorithm outputs a tab-separated list of attributes, ranked
-by the most important feature first. The <i> method </i> parameter
-allows a choice between the Maximum Information Difference (MID) and
-Mutual Information Quotient (MIQ) feature evaluation criteria, which
+form, i.e., 1, 2, 3.... rather than 'forest' or 'urban'. Also, the
+attribute table should not contain any missing values because this
+causes an erroneous mRMR result.
+
+<p>The algorithm outputs a tab-separated list of attributes, ranked by
+the most important feature first. The <i> method </i> parameter allows a
+choice between the Maximum Information Difference (MID) and Mutual
+Information Quotient (MIQ) feature evaluation criteria, which
 respectively represent the relevancy and redundancy of the features. The
 algorithm also shows the ranking of the features based on the
 conventional maximum relevance method. Additional user options include
@@ -38,14 +40,14 @@
 
 <h2>EXAMPLE</h2>
 
-v.mrmr.py vector=vector_layer layer=1 thres=1.0
-nfeatures=50 nsamples=10000 maxvar=10000 method=MID
+v.mrmr.py vector=vector_layer layer=1 thres=1.0 nfeatures=50
+nsamples=10000 maxvar=10000 method=MID
 
 <h2>REFERENCES</h2>
 
-Peng, H.; Fulmi Long; Ding, C., "Feature selection
-based on mutual information criteria of max-dependency, max-relevance,
-and min-redundancy," in Pattern Analysis and Machine Intelligence, IEEE
+Peng, H.; Fulmi Long; Ding, C., "Feature selection based on mutual
+information criteria of max-dependency, max-relevance, and
+min-redundancy," in Pattern Analysis and Machine Intelligence, IEEE
 Transactions on , vol.27, no.8, pp.1226-1238, Aug. 2005
 
 <h2>AUTHOR</h2>