|
wolffd@0
|
1 function [model, partition_size] = fit_partitioned_model(...
|
|
wolffd@0
|
2 inputs, outputs, selectors, sel_sizes, min_size, partition_names, fn_name, varargin)
|
|
wolffd@0
|
3 %function [models, partition_sizes] = fit_partitioned_model(...
|
|
wolffd@0
|
4 % inputs, outputs, selectors, sel_sizes, min_size, partition_names, fn_name, varargin)
|
|
wolffd@0
|
5 %
|
|
wolffd@0
|
6 % Fit models to different subsets (columns) of the input/output data,
|
|
wolffd@0
|
7 % as chosen by the selectors matrix. If there is only output data, set input=[].
|
|
wolffd@0
|
8 % If there is less than min_size data in partition i,
|
|
wolffd@0
|
9 % we set model{i} = []
|
|
wolffd@0
|
10 %
|
|
wolffd@0
|
11 % Example:
|
|
wolffd@0
|
12 % selectors = [1 2 1 1 1
|
|
wolffd@0
|
13 % 1 2 2 1 2]
|
|
wolffd@0
|
14 % sel_sizes = [2 2] so there are 4 models: (1,1), (2,1), (1,2), (2,2)
|
|
wolffd@0
|
15 % We fit model{1} to data from columns 1,4
|
|
wolffd@0
|
16 % We fit model{2} to no data
|
|
wolffd@0
|
17 % We fit model{3} to data from column 3,5
|
|
wolffd@0
|
18 % We fit model{4} to data from column 2 (assuming min_size <= 1)
|
|
wolffd@0
|
19 %
|
|
wolffd@0
|
20 % For each partition, we call the specified function with the specified arguments
|
|
wolffd@0
|
21 % as follows:
|
|
wolffd@0
|
22 % model{i} = fn(input(:,cols{i}), output(:,cols{i}), args)
|
|
wolffd@0
|
23 % (We omit input if [])
|
|
wolffd@0
|
24 % partition_size(i) is the amount of data in the i'th partition.
|
|
wolffd@0
|
25 %
|
|
wolffd@0
|
26 % Example use: row 1 of selectors is whether an object is present/absent
|
|
wolffd@0
|
27 % and row 2 is the location.
|
|
wolffd@0
|
28 %
|
|
wolffd@0
|
29 % Demo:
|
|
wolffd@0
|
30 % inputs = 1:5; outputs = 6:10; selectors = as above
|
|
wolffd@0
|
31 % fn = 'fit_partitioned_model_testfn';
|
|
wolffd@0
|
32 % [model, partition_size] = fit_partitioned_model(inputs, outputs, selectors, [2 2], fn)
|
|
wolffd@0
|
33 % should produce
|
|
wolffd@0
|
34 % model{1}.input = [1 4], model{1}.output = [6 9]
|
|
wolffd@0
|
35 % model{2} = []
|
|
wolffd@0
|
36 % model{3}.input = [3 5], model{3}.output = [8 10],
|
|
wolffd@0
|
37 % model{4}.input = [2], model{3}.output = [7],
|
|
wolffd@0
|
38 % partition_size = [2 0 2 1]
|
|
wolffd@0
|
39
|
|
wolffd@0
|
40
|
|
wolffd@0
|
41 sel_ndx = subv2ind(sel_sizes, selectors');
|
|
wolffd@0
|
42 Nmodels = prod(sel_sizes);
|
|
wolffd@0
|
43 model = cell(1, Nmodels);
|
|
wolffd@0
|
44 partition_size = zeros(1, Nmodels);
|
|
wolffd@0
|
45 for m=1:Nmodels
|
|
wolffd@0
|
46 ndx = find(sel_ndx==m);
|
|
wolffd@0
|
47 partition_size(m) = length(ndx);
|
|
wolffd@0
|
48 if ~isempty(partition_names) % & (partition_size(m) < min_size)
|
|
wolffd@0
|
49 fprintf('partition %s has size %d, min size = %d\n', ...
|
|
wolffd@0
|
50 partition_names{m}, partition_size(m), min_size);
|
|
wolffd@0
|
51 end
|
|
wolffd@0
|
52 if partition_size(m) >= min_size
|
|
wolffd@0
|
53 if isempty(inputs)
|
|
wolffd@0
|
54 model{m} = feval(fn_name, outputs(:, ndx), varargin{:});
|
|
wolffd@0
|
55 else
|
|
wolffd@0
|
56 model{m} = feval(fn_name, inputs(:,ndx), outputs(:, ndx), varargin{:});
|
|
wolffd@0
|
57 end
|
|
wolffd@0
|
58 end
|
|
wolffd@0
|
59 end
|
