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commit 0045cdea0417577a15ca52e08d61df850ce8490f Author: Bas Couwenberg <[email protected]> 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 <[email protected]> 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> -- Alioth's /usr/local/bin/git-commit-notice on /srv/git.debian.org/git/pkg-grass/pktools.git _______________________________________________ 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