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sebastic-guest pushed a commit to branch master
in repository pktools.

commit 0045cdea0417577a15ca52e08d61df850ce8490f
Author: Bas Couwenberg <sebas...@xs4all.nl>
Date:   Sun Dec 7 02:04:36 2014 +0100

    Add man page for pkfsann.
---
 debian/changelog         |   2 +-
 debian/man/pkfsann.1.xml | 346 +++++++++++++++++++++++++++++++++++++++++++++++
 2 files changed, 347 insertions(+), 1 deletion(-)

diff --git a/debian/changelog b/debian/changelog
index 7de4617..534cb50 100644
--- a/debian/changelog
+++ b/debian/changelog
@@ -5,7 +5,7 @@ pktools (2.6.1-1) UNRELEASED; urgency=medium
   * Remove libbase package, library no longer installed.
   * Add man page for pkann, pkascii2img, pkascii2ogr, pkcomposite, pkcreatect,
     pkcrop, pkdiff, pkdsm2shadow, pkdumpimg, pkdumpogr, pkegcs, pkextract,
-    pkfillnodata, pkfilter, pkfilterascii, pkfilterdem.
+    pkfillnodata, pkfilter, pkfilterascii, pkfilterdem, pkfsann.
 
  -- Bas Couwenberg <sebas...@xs4all.nl>  Wed, 03 Dec 2014 21:16:31 +0100
 
diff --git a/debian/man/pkfsann.1.xml b/debian/man/pkfsann.1.xml
new file mode 100644
index 0000000..a6aee70
--- /dev/null
+++ b/debian/man/pkfsann.1.xml
@@ -0,0 +1,346 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<!DOCTYPE refentry PUBLIC "-//OASIS//DTD DocBook XML V4.4//EN" 
"http://www.oasis-open.org/docbook/xml/4.4/docbookx.dtd";>
+<refentry id='pkfsann'>
+
+  <refmeta>
+    <refentrytitle>pkfsann</refentrytitle>
+    <manvolnum>1</manvolnum>
+  </refmeta>
+
+  <refnamediv>
+    <refname>pkfsann</refname>
+    <refpurpose>feature selection for nn classifier</refpurpose>
+  </refnamediv>
+
+  <refsynopsisdiv id='synopsis'>
+    <cmdsynopsis>
+      <command>pkfsann</command>
+      <arg choice='plain'><option>-t</option> 
<replaceable>training</replaceable></arg>
+      <arg choice='plain'><option>-n</option> 
<replaceable>number</replaceable></arg>
+      <arg choice='opt'><replaceable>options</replaceable></arg>
+      <arg choice='opt'><replaceable>advanced options</replaceable></arg>
+    </cmdsynopsis>
+  </refsynopsisdiv>
+
+  <refsect1 id='description'>
+    <title>DESCRIPTION</title>
+    <para>
+      Classification problems dealing with high dimensional input data can be
+      challenging due to the Hughes phenomenon.
+      Hyperspectral data, for instance, can have hundreds of spectral bands and
+      require special attention when being classified.
+      In particular when limited training data are available,
+      the classification of such data can be problematic without reducing the
+      dimension.
+    </para>
+    <para>
+      <command>pkfsann</command> implements a number of feature selection
+      techniques, among which a sequential floating forward search (SFFS).
+      Also consider the SVM classifier implemented in
+      <citerefentry>
+        <refentrytitle>pksvm</refentrytitle>
+        <manvolnum>1</manvolnum>
+      </citerefentry>,
+      which has been shown to be more robust to this type of problem than 
others. 
+    </para>
+  </refsect1>
+
+  <refsect1 id='options'>
+    <title>OPTIONS</title>
+    <variablelist>
+
+      <varlistentry>
+        <term><option>-t</option> <replaceable>filename</replaceable></term>
+        <term><option>--training</option> 
<replaceable>filename</replaceable></term>
+        <listitem>
+          <para>
+            training vector file.
+            A single vector file contains all training features
+            (must be set as: B0, B1, B2,...) for all classes
+            (class numbers identified by label option).
+            Use multiple training files for bootstrap aggregation
+            (alternative to the bag and bsize options,
+            where a random subset is taken from a single training file)
+          </para>
+        </listitem>
+      </varlistentry>
+
+      <varlistentry>
+        <term><option>-n</option> <replaceable>number</replaceable></term>
+        <term><option>--nf</option> <replaceable>number</replaceable></term>
+        <listitem>
+          <para>
+            number of features to select
+            (0 to select optimal number,
+            see also <option>--ecost</option> option)
+          </para>
+        </listitem>
+      </varlistentry>
+
+      <varlistentry>
+        <term><option>-i</option> <replaceable>filename</replaceable></term>
+        <term><option>--input</option> 
<replaceable>filename</replaceable></term>
+        <listitem>
+          <para>
+            input test set (leave empty to perform a cross validation based on
+            training only)
+          </para>
+        </listitem>
+      </varlistentry>
+
+      <varlistentry>
+        <term><option>-v</option> <replaceable>level</replaceable></term>
+        <term><option>--verbose</option> 
<replaceable>level</replaceable></term>
+        <listitem>
+          <para>
+            set to: 0 (results only), 1 (confusion matrix), 2 (debug)
+          </para>
+        </listitem>
+      </varlistentry>
+
+    </variablelist>
+    
+    <para>Advanced options</para>
+    <variablelist>
+
+      <varlistentry>
+        <term><option>-tln</option> <replaceable>layer</replaceable></term>
+        <term><option>--tln</option> <replaceable>layer</replaceable></term>
+        <listitem>
+          <para>
+            training layer name(s)
+          </para>
+        </listitem>
+      </varlistentry>
+
+      <varlistentry>
+        <term><option>-label</option> 
<replaceable>attribute</replaceable></term>
+        <term><option>--label</option> 
<replaceable>attribute</replaceable></term>
+        <listitem>
+          <para>
+            identifier for class label in training vector file.
+            (default: label)
+          </para>
+        </listitem>
+      </varlistentry>
+
+      <varlistentry>
+        <term><option>--balance</option> <replaceable>size</replaceable></term>
+        <listitem>
+          <para>
+            balance the input data to this number of samples for each class
+            (default: 0)
+          </para>
+        </listitem>
+      </varlistentry>
+
+      <varlistentry>
+        <term><option>-random</option></term>
+        <term><option>--random</option></term>
+        <listitem>
+          <para>
+            in case of balance, randomize input data
+          </para>
+        </listitem>
+      </varlistentry>
+
+      <varlistentry>
+        <term><option>-min</option> <replaceable>number</replaceable></term>
+        <term><option>--min</option> <replaceable>number</replaceable></term>
+        <listitem>
+          <para>
+            if number of training pixels is less then min,
+            do not take this class into account
+          </para>
+        </listitem>
+      </varlistentry>
+
+      <varlistentry>
+        <term><option>-b</option> <replaceable>band</replaceable></term>
+        <term><option>--band</option> <replaceable>band</replaceable></term>
+        <listitem>
+          <para>
+            band index (starting from 0, either use band option or use start
+            to end)
+          </para>
+        </listitem>
+      </varlistentry>
+
+      <varlistentry>
+        <term><option>-s</option> <replaceable>band</replaceable></term>
+        <term><option>--start</option> <replaceable>band</replaceable></term>
+        <listitem>
+          <para>
+            start band sequence number
+            (default: 0)
+          </para>
+        </listitem>
+      </varlistentry>
+
+      <varlistentry>
+        <term><option>-e</option> <replaceable>band</replaceable></term>
+        <term><option>--end</option> <replaceable>band</replaceable></term>
+        <listitem>
+          <para>
+            end band sequence number (set to 0 to include bands)
+          </para>
+        </listitem>
+      </varlistentry>
+
+      <varlistentry>
+        <term><option>--offset</option> <replaceable>value</replaceable></term>
+        <listitem>
+          <para>
+            offset value for each spectral band input features:
+            refl[band]=(DN[band]-offset[band])/scale[band]
+          </para>
+        </listitem>
+      </varlistentry>
+
+      <varlistentry>
+        <term><option>--scale</option> <replaceable>value</replaceable></term>
+        <listitem>
+          <para>
+            scale value for each spectral band input features:
+            refl=(DN[band]-offset[band])/scaleband
+            (use 0 if scale min and max in each band to -1.0 and 1.0)
+          </para>
+        </listitem>
+      </varlistentry>
+
+      <varlistentry>
+        <term><option>-a</option> <replaceable>0|1|2</replaceable></term>
+        <term><option>--aggreg</option> <replaceable>0|1|2</replaceable></term>
+        <listitem>
+          <para>
+            how to combine aggregated classifiers, see also
+            <option>--rc</option> option
+            (0: no aggregation, 1: sum rule, 2: max rule).
+          </para>
+        </listitem>
+      </varlistentry>
+
+      <varlistentry>
+        <term><option>-sm</option> <replaceable>method</replaceable></term>
+        <term><option>--sm</option> <replaceable>method</replaceable></term>
+        <listitem>
+          <para>
+            feature selection method
+            (sffs=sequential floating forward search,
+            sfs=sequential forward search, sbs, sequential backward search,
+            bfs=brute force search)
+          </para>
+        </listitem>
+      </varlistentry>
+
+      <varlistentry>
+        <term><option>-ecost</option> <replaceable>value</replaceable></term>
+        <term><option>--ecost</option> <replaceable>value</replaceable></term>
+        <listitem>
+          <para>
+            epsilon for stopping criterion in cost function to determine
+            optimal number of features
+          </para>
+        </listitem>
+      </varlistentry>
+
+      <varlistentry>
+        <term><option>-cv</option> <replaceable>value</replaceable></term>
+        <term><option>--cv</option> <replaceable>value</replaceable></term>
+        <listitem>
+          <para>
+            n-fold cross validation mode (default: 0)
+          </para>
+        </listitem>
+      </varlistentry>
+
+      <varlistentry>
+        <term><option>-c</option> <replaceable>name</replaceable></term>
+        <term><option>--class</option> <replaceable>name</replaceable></term>
+        <listitem>
+          <para>
+            list of class names.
+          </para>
+        </listitem>
+      </varlistentry>
+
+      <varlistentry>
+        <term><option>-r</option> <replaceable>value</replaceable></term>
+        <term><option>--reclass</option> 
<replaceable>value</replaceable></term>
+        <listitem>
+          <para>
+            list of class values (use same order as in
+            <option>--class</option> option).
+          </para>
+        </listitem>
+      </varlistentry>
+
+      <varlistentry>
+        <term><option>-n</option> <replaceable>number</replaceable></term>
+        <term><option>--nneuron</option> 
<replaceable>number</replaceable></term>
+        <listitem>
+          <para>
+            number of neurons in hidden layers in neural network (multiple
+            hidden layers are set by defining multiple number of neurons:
+            <option>-nn</option> 15 <option>-nn</option> 1, default is one
+            hidden layer with 5 neurons)
+          </para>
+        </listitem>
+      </varlistentry>
+
+      <varlistentry>
+        <term><option>--connection</option> 
<replaceable>0|1</replaceable></term>
+        <listitem>
+          <para>
+            connection rate (default: 1.0 for a fully connected network)
+          </para>
+        </listitem>
+      </varlistentry>
+
+      <varlistentry>
+        <term><option>-w</option> <replaceable>weights</replaceable></term>
+        <term><option>--weights</option> 
<replaceable>weights</replaceable></term>
+        <listitem>
+          <para>
+            weights for neural network.
+            Apply to fully connected network only, starting from first input
+            neuron to last output neuron, including the bias neurons (last
+            neuron in each but last layer)
+          </para>
+        </listitem>
+      </varlistentry>
+
+      <varlistentry>
+        <term><option>-l</option> <replaceable>rate</replaceable></term>
+        <term><option>--learning</option> 
<replaceable>rate</replaceable></term>
+        <listitem>
+          <para>
+            learning rate (default: 0.7)
+          </para>
+        </listitem>
+      </varlistentry>
+
+      <varlistentry>
+        <term><option>--maxit</option> <replaceable>number</replaceable></term>
+        <listitem>
+          <para>
+            number of maximum iterations (epoch) (default: 500)
+          </para>
+        </listitem>
+      </varlistentry>
+
+    </variablelist>
+
+  </refsect1>
+
+  <refsect1 id='see-also'>
+    <title>SEE ALSO</title>
+
+    <citerefentry>
+      <refentrytitle>pksvm</refentrytitle>
+      <manvolnum>1</manvolnum>
+    </citerefentry>
+
+  </refsect1>
+
+</refentry>

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