Revision: 19688
http://sourceforge.net/p/gate/code/19688
Author: ggorrell
Date: 2016-10-17 13:49:12 +0000 (Mon, 17 Oct 2016)
Log Message:
-----------
Beginning the ML section with a link to the Learning Framework.
Modified Paths:
--------------
userguide/trunk/machine-learning.tex
Modified: userguide/trunk/machine-learning.tex
===================================================================
--- userguide/trunk/machine-learning.tex 2016-10-17 09:48:28 UTC (rev
19687)
+++ userguide/trunk/machine-learning.tex 2016-10-17 13:49:12 UTC (rev
19688)
@@ -5,17 +5,21 @@
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-This \chapthing\ presents machine learning PRs available in
-GATE. Currently, two PRs are available:
+This \chapthing\ describes older machine learning PRs available in
+GATE. The most up to date and best supported machine learning PR in
+GATE is the \textbf{Learning Framework}. This is available on Github
+at the address below:
+https://github.com/GateNLP/gateplugin-LearningFramework
+
+The two historical PRs described in this chapter are as follows:
+
\begin{itemize}
-\item{The \textbf{Batch Learning PR} (in the \textbf{Learning} plugin) is
GATE's
-most comprehensive and developed machine learning offering. It is specifically
-targetted at NLP tasks including text classification, chunk learning (e.g. for
-named entity recognition) and relation learning. It integrates LibSVM for
-improved speed, along with the PAUM algorithm, offering very competitive
-performance and speed. It also offers a Weka interface. It is documented in
+\item{The \textbf{Batch Learning PR} (in the \textbf{Learning} plugin) is
targetted at NLP tasks including text classification, chunk learning (e.g. for
+named entity recognition) and relation learning. It integrates LibSVM
+for improved speed, along with the PAUM algorithm. It also offers a
+Weka interface. It is documented in
Section~\ref{sec:ml:batch-learning-pr}.}
%It is introduced briefly
%in section~\ref{sect:learning-pr} and documented more fully in
@@ -23,18 +27,19 @@
%short introduction to machine learning, in which concepts are defined.}
\item{The \textbf{Machine Learning PR} (in the \textbf{Machine\_Learning}
plugin)
-is GATE's older machine learning offering. It offers wrappers for Maxent, Weka
-and SVM Light. It is documented in Section~\ref{sec:ml:machine-learning-pr}.}
+is GATE's even older machine learning offering. It offers wrappers for
+Maxent, Weka and SVM Light. It is documented in
+Section~\ref{sec:ml:machine-learning-pr}.}
\end{itemize}
To use GATE in conjunction with machine learning technologies that are
-not supported by the two PRs described here, you would need to export
-your data from GATE to use with the ML technology outside of GATE. One
-possibility for doing that would be to use the \textbf{Configurable
-Exporter PR} described in
-Section~\ref{sec:misc-creole:confexport}. The \textbf{Batch Learning PR}
-also offers data export functionality.
+not supported by a GATE PR, you would need to export your data from
+GATE to use with the ML technology outside of GATE. One possibility
+for doing that would be to use the \textbf{Configurable Exporter PR}
+described in
+Section~\ref{sec:misc-creole:confexport}. The \textbf{Batch Learning
+PR} also offers data export functionality.
The rest of the \chapthing\ is organised as follows. Section
\ref{sec:ml:generalities} introduces machine learning in general, focusing on
the
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