From c3c509a45ab2c4bd08a0338fa37506ce57a2db87 Mon Sep 17 00:00:00 2001 From: Petr Baudis Date: Tue, 9 Mar 2010 22:35:14 +0100 Subject: [PATCH] tex: Data Extraction - tidy up --- tex/gostyle.tex | 9 +++------ 1 file changed, 3 insertions(+), 6 deletions(-) diff --git a/tex/gostyle.tex b/tex/gostyle.tex index 5b4773a..ac312f5 100644 --- a/tex/gostyle.tex +++ b/tex/gostyle.tex @@ -359,16 +359,13 @@ should yield similar moves characteristics. \section{Data Extraction} \label{pattern-vectors} -In addition to the explicit expert knowledge, we use the data obtained by... -TODO rozvest uvod, nemuze se zacinat jenom As the input... - -As the input, we assume a~collection of game records\footnote{We +As the input of our analysis, we use large collections of game records\footnote{We use the SGF format (TODO) in our implementation.} organized by player names. - In order to generate the required compact description of most frequently played moves, we construct a set of $n$ most occuring patterns (\emph{top patterns}) -across all players and games from the database\footnote{We use $n=500$ in our analysis.}. +across all players and games from the database.\footnote{We use $n=500$ in our analysis.} + For each player, we then count how many times was each of those $n$ patterns played during all his games and finally assign him a~{\em pattern vector} $\vec p$ of dimension $n$, with each dimension corresponding to the relative number of occurences of a given pattern -- 2.11.4.GIT