precision.m.svn-base

a function inside machine learning

function p = precision(trueY, predictedY, ranking) 
% Compute the precision of a set of predictions
%
% Usage: p = precision(trueY, predictedY, ranking) 
% Inputs/Outputs:  
%   trueY - column vector of binary labels 
%   predictedY - column vector of predicted labels 
%   rankings (optional) - rankings of predicted labels 
%
%   p - the precision
%
% Copyright (C) 2006 Charanpal Dhanjal 

% This library is free software; you can redistribute it and/or
% modify it under the terms of the GNU Lesser General Public
% License as published by the Free Software Foundation; either
% version 2.1 of the License, or (at your option) any later version.
% 
% This library is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
% Lesser General Public License for more details.
% 
% You should have received a copy of the GNU Lesser General Public
% License along with this library; if not, write to the Free Software
% Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301
% USA

if (nargin < 2)
    fprintf('%s\n', help(sprintf('%s', mfilename)));
    error('Incorrect number of inputs - see above usage instructions.');
end

%Assume a positive is anything greater than zero, negative is zero or less 
trueYBin = (trueY > 0); 
predictedYBin = (predictedY > 0); 

sumPredY = sum(predictedYBin == 1); 

if sumPredY ~= 0 
    p = length(intersect(find(trueY == predictedY), find(trueYBin == 1)))/sumPredY;
else 
    p = 0; 
end