annotate toolboxes/FullBNT-1.0.7/bnt/CPDs/@softmax_CPD/set_fields.m @ 0:cc4b1211e677 tip

initial commit to HG from Changeset: 646 (e263d8a21543) added further path and more save "camirversion.m"
author Daniel Wolff
date Fri, 19 Aug 2016 13:07:06 +0200
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Daniel@0 1 function CPD = set_params(CPD, varargin)
Daniel@0 2 % SET_PARAMS Set the parameters (fields) for a softmax_CPD object
Daniel@0 3 % CPD = set_params(CPD, name/value pairs)
Daniel@0 4 %
Daniel@0 5 % The following optional arguments can be specified in the form of name/value pairs:
Daniel@0 6 % (Let ns(i) be the size of node i, X = ns(X), Y = ns(Y), Q1=ns(dps(1)), Q2=ns(dps(2)), ...
Daniel@0 7 % where dps are the discrete parents; if there are no discrete parents, we set Q1=1.)
Daniel@0 8 %
Daniel@0 9 % weights - (W(:,j,a,b,...) - W(:,j',a,b,...)) is ppn to dec. boundary
Daniel@0 10 % between j,j' given Q1=a,Q2=b,... [ randn(X,Y,Q1,Q2,...) ]
Daniel@0 11 % offset - (offset(j,a,b,...) - offset(j',a,b,...)) is the offset to dec. boundary
Daniel@0 12 % between j,j' given Q1=a,Q2=b,... [ randn(Y,Q1,Q2,...) ]
Daniel@0 13 % clamped - 'yes' means don't adjust params during learning ['no']
Daniel@0 14 % max_iter - the maximum number of steps to take [10]
Daniel@0 15 % verbose - 'yes' means print the LL at each step of IRLS ['no']
Daniel@0 16 % wthresh - convergence threshold for weights [1e-2]
Daniel@0 17 % llthresh - convergence threshold for log likelihood [1e-2]
Daniel@0 18 % approx_hess - 'yes' means approximate the Hessian for speed ['no']
Daniel@0 19 %
Daniel@0 20 % e.g., CPD = set_params(CPD,'offset', zeros(ns(i),1));
Daniel@0 21
Daniel@0 22 args = varargin;
Daniel@0 23 nargs = length(args);
Daniel@0 24 glimsz = prod(CPD.sizes(CPD.dpndx));
Daniel@0 25 for i=1:2:nargs
Daniel@0 26 switch args{i},
Daniel@0 27 case 'discrete', str='nothing to do';
Daniel@0 28 case 'clamped', CPD = set_clamped(CPD, strcmp(args{i+1}, 'yes'));
Daniel@0 29 case 'max_iter', CPD.max_iter = args{i+1};
Daniel@0 30 case 'verbose', CPD.verbose = strcmp(args{i+1}, 'yes');
Daniel@0 31 case 'max_iter', CPD.max_iter = args{i+1};
Daniel@0 32 case 'wthresh', CPD.wthresh = args{i+1};
Daniel@0 33 case 'llthresh', CPD.llthresh = args{i+1};
Daniel@0 34 case 'approx_hess', CPD.approx_hess = strcmp(args{i+1}, 'yes');
Daniel@0 35 case 'weights', for q=1:glimsz, CPD.glim{q}.w1 = args{i+1}(:,:,q); end;
Daniel@0 36 case 'offset',
Daniel@0 37 if glimsz == 1
Daniel@0 38 CPD.glim{1}.b1 = args{i+1};
Daniel@0 39 else
Daniel@0 40 for q=1:glimsz, CPD.glim{q}.b1 = args{i+1}(:,q); end;
Daniel@0 41 end
Daniel@0 42 otherwise,
Daniel@0 43 error(['invalid argument name ' args{i}]);
Daniel@0 44 end
Daniel@0 45 end