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commit e3f904bc67cd050586851ddcf3312d1b97c831de
Author: Bas Couwenberg <sebas...@xs4all.nl>
Date:   Thu Dec 11 23:46:52 2014 +0100

    Add man page for pkregann.
---
 debian/changelog          |   2 +-
 debian/man/pkregann.1.xml | 220 ++++++++++++++++++++++++++++++++++++++++++++++
 2 files changed, 221 insertions(+), 1 deletion(-)

diff --git a/debian/changelog b/debian/changelog
index db8d84a..55c8387 100644
--- a/debian/changelog
+++ b/debian/changelog
@@ -6,7 +6,7 @@ pktools (2.6.1-1) UNRELEASED; urgency=medium
   * Add man page for pkann, pkascii2img, pkascii2ogr, pkcomposite, pkcreatect,
     pkcrop, pkdiff, pkdsm2shadow, pkdumpimg, pkdumpogr, pkegcs, pkextract,
     pkfillnodata, pkfilter, pkfilterascii, pkfilterdem, pkfsann, pkfssvm,
-    pkgetmask, pkinfo, pklas2img, pkoptsvm, pkpolygonize.
+    pkgetmask, pkinfo, pklas2img, pkoptsvm, pkpolygonize, pkregann.
 
  -- Bas Couwenberg <sebas...@xs4all.nl>  Wed, 03 Dec 2014 21:16:31 +0100
 
diff --git a/debian/man/pkregann.1.xml b/debian/man/pkregann.1.xml
new file mode 100644
index 0000000..559880d
--- /dev/null
+++ b/debian/man/pkregann.1.xml
@@ -0,0 +1,220 @@
+<?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='pkregann'>
+
+  <refmeta>
+    <refentrytitle>pkregann</refentrytitle>
+    <manvolnum>1</manvolnum>
+  </refmeta>
+
+  <refnamediv>
+    <refname>pkregann</refname>
+    <refpurpose>regression with artificial neural network (multi-layer 
perceptron)</refpurpose>
+  </refnamediv>
+
+  <refsynopsisdiv id='synopsis'>
+    <cmdsynopsis>
+      <command>pkregann</command>
+      <arg choice='plain'><option>-i</option> 
<replaceable>input</replaceable></arg>
+      <arg choice='plain'><option>-t</option> 
<replaceable>training</replaceable></arg>
+      <arg choice='opt'><option>-ic</option> 
<replaceable>col</replaceable></arg>
+      <arg choice='opt'><option>-oc</option> 
<replaceable>col</replaceable></arg>
+      <arg choice='plain'><option>-o</option> 
<replaceable>output</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>
+      <command>pkregann</command> performs a regression based on an artificial
+      neural network.
+      The regression is trained from the input (<option>-ic</option>) and
+      output (<option>-oc</option>) columns in a training text file.
+      Each row in the training file represents one sampling unit.
+      Multi-dimensional input features can be defined with multiple input
+      options (e.g.,
+      <option>-ic</option> <replaceable>0</replaceable>
+      <option>-ic</option> <replaceable>1</replaceable>
+      <option>-ic</option> <replaceable>2</replaceable>
+      for three dimensional features).
+    </para>
+  </refsect1>
+
+  <refsect1 id='options'>
+    <title>OPTIONS</title>
+    <variablelist>
+
+      <varlistentry>
+        <term><option>-i</option> <replaceable>filename</replaceable></term>
+        <term><option>--input</option> 
<replaceable>filename</replaceable></term>
+        <listitem>
+          <para>
+            input ASCII file
+          </para>
+        </listitem>
+      </varlistentry>
+
+      <varlistentry>
+        <term><option>-t</option> <replaceable>filename</replaceable></term>
+        <term><option>--training</option> 
<replaceable>filename</replaceable></term>
+        <listitem>
+          <para>
+            training ASCII file (each row represents one sampling unit.
+            Input features should be provided as columns, followed by output)
+          </para>
+        </listitem>
+      </varlistentry>
+
+      <varlistentry>
+        <term><option>-o</option> <replaceable>filename</replaceable></term>
+        <term><option>--output</option> 
<replaceable>filename</replaceable></term>
+        <listitem>
+          <para>
+            output ASCII file for result
+          </para>
+        </listitem>
+      </varlistentry>
+
+      <varlistentry>
+        <term><option>-ic</option> <replaceable>col</replaceable></term>
+        <term><option>--inputCols</option> 
<replaceable>col</replaceable></term>
+        <listitem>
+          <para>
+            input columns (e.g., for three dimensional input data in first
+            three columns use:
+            <option>-ic</option> <replaceable>0</replaceable>
+            <option>-ic</option> <replaceable>1</replaceable>
+            <option>-ic</option> <replaceable>2</replaceable>
+          </para>
+        </listitem>
+      </varlistentry>
+
+      <varlistentry>
+        <term><option>-oc</option> <replaceable>col</replaceable></term>
+        <term><option>--outputCols</option> 
<replaceable>col</replaceable></term>
+        <listitem>
+          <para>
+            output columns (e.g., for two dimensional output in columns 3 and 4
+            (starting from <replaceable>0</replaceable>) use:
+            <option>-oc</option> <replaceable>3</replaceable>
+            <option>-oc</option> <replaceable>4</replaceable>
+          </para>
+        </listitem>
+      </varlistentry>
+
+      <varlistentry>
+        <term><option>-from</option> <replaceable>row</replaceable></term>
+        <term><option>--from</option> <replaceable>row</replaceable></term>
+        <listitem>
+          <para>
+            start from this row in training file (start from 0)
+          </para>
+        </listitem>
+      </varlistentry>
+
+      <varlistentry>
+        <term><option>-to</option> <replaceable>row</replaceable></term>
+        <term><option>--to</option> <replaceable>row</replaceable></term>
+        <listitem>
+          <para>
+            read until this row in training file (start from 0 or set leave 0
+            as default to read until end of file)
+          </para>
+        </listitem>
+      </varlistentry>
+
+      <varlistentry>
+        <term><option>-cv</option> <replaceable>size</replaceable></term>
+        <term><option>--cv</option> <replaceable>size</replaceable></term>
+        <listitem>
+          <para>
+            n-fold cross validation mode
+          </para>
+        </listitem>
+      </varlistentry>
+
+      <varlistentry>
+        <term><option>-nn</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>-n</option> <replaceable>15</replaceable>
+            <option>-n</option> <replaceable>1</replaceable>,
+            default is one hidden layer with 5 neurons)
+          </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>--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>--connection</option> 
<replaceable>rate</replaceable></term>
+        <listitem>
+          <para>
+            connection rate (default: 1.0 for a fully connected network)
+          </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>
+
+</refentry>

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