📄 som_drsignif.m
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function sig = som_drsignif(sigmea,Cm)% SOM_DRSIGNIF Significance measure from confusion matrix between two clusters and a rule.%% sig = som_drsignif(sigmea,Cm)% % sigmea (string) significance measure: 'accuracy', % 'mutuconf' (default), or 'accuracyI'.% (See definitions below).% Cn Vectorized confusion matrix, or a matrix of such vectors.% (vector) [a, c, b, d] (see below)% (matrix) [[a1,c1,b1,d1], ..., [an,cn,bn,dn]]%% sig (vector) length=n, significance values %% The confusion matrix Cm below between group (G) and contrast group (not G)% and rule (true - false) is used to determine the significance values:%% G not G % --------------- accuracy = (a+d) / (a+b+c+d)% true | a | b | % |-------------- mutuconf = a*a / ((a+b)(a+c)) % false | c | d | % --------------- accuracyI = a / (a+b+c)%% See also SOM_DREVAL, SOM_DRMAKE.% Contributed to SOM Toolbox 2.0, March 4th, 2002 by Juha Vesanto% Copyright (c) by Juha Vesanto% http://www.cis.hut.fi/projects/somtoolbox/% Version 2.0beta juuso 040302%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% input argumentstrue_x = Cm(:,1); % x = in groupfalse_x = Cm(:,2); % false = rule is falsetrue_y = Cm(:,3); % true = rule is truefalse_y = Cm(:,4); % y = not in grouptrue_items = true_x + true_y; x_items = true_x + false_x; all_items = true_x + false_x + true_y + false_y; true_or_x = x_items + true_items - true_x; switch sigmea, case 'mutuconf', % mutual confidence, or relevance (as defined in WSOM2001 paper) sig = zeros(size(true_x)); i = find(true_items>0 & x_items>0); sig(i) = (true_x(i).^2) ./ (true_items(i).*x_items(i)); case 'accuracy', % accuracy sig = (true_x + false_y) ./ all_items;case 'accuracyI', % accuracy such that false_y is left out of consideration sig = true_x./true_or_x;otherwise, error(['Unrecognized significance measures: ' sigmea]);end return;
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