root/MachineLearningWithMATLAB/Regression_FuelEconomy/dummytable.m @ 11
| 10 | anderm8 | function Tdummy = dummytable(T)
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% Tdummy = dummytable(T) - convert categorical variables in table to dummy
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% variables
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%
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% This functions takes the categorical variables in a table and converts
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% them to separate dummy variables with intelligent names. This way they
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% can be used in the Classification Learner App and the variable names make
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% sense for feature selection, etc.
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%
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% Usage:
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%
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% Tdummy = dummytable(T)
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%
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% Inputs:
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%
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% T: Table with categoricals or categorical variable
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%
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% Outputs:
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%
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% Tdummy: T with categorical variables turned into dummy variables with
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% intelligent names
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%
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% Example:
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%
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% % Simple Table
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% T = table(rand(10,1),categorical(cellstr('rbbgbgbbgr'.')),...
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% 'VariableNames',{'Percent','Color'});
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% disp(T)
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%
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% % Turn it into a dummy table
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% Tdummy = dummytable(T);
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% disp(Tdummy)
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%
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% See Also: dummyvar, table, categorical, classificationLearner
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% Copyright 2015 The MathWorks, Inc.
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% Sean de Wolski Apr 13, 2014
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% Error checking
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narginchk(1,1)
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validateattributes(T,{'categorical', 'table'},{},mfilename,'T',1);
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% If it's a categorical, do out best to convert it to a table with an
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% intelligent variable name
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if iscategorical(T)
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% Try to use existing variable name
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cname = inputname(1);
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if isempty(cname)
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% It's a MATLAB Expression, default to Var1
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cname = 'Var1';
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end
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T = table(T,'VariableNames',{cname});
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end
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% Identify categoricals and their names
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cats = varfun(@iscategorical,T,'OutputFormat','uniform');
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% Short circuit if there are no categoricals
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if ~any(cats)
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Tdummy = T;
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return
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end
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% Store everything in a cell. w will be the total width of the table
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% with each variable dummyvar'd
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w = nnz(~cats)+sum(varfun(@(x)numel(categories(x)),T(:,cats),'OutputFormat','uniform'));
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% Preallocate storage
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datastorage = cell(1,w);
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namestorage = cell(1,w);
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% Engine
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idx = 0; % Start nowhere in cell
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for ii = 1:width(T)
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idx = idx+1;
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% Loop over table deciding what to do with each variable
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if cats(ii)
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% It's a categorical,
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% Extract it and build keep its categories and dummyvar
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Tii = T{:,ii};
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categoriesii = categories(Tii)';
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ncatii = numel(categoriesii); % How many?
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% Build dummy var as a row cell with columns in each
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dvii = num2cell(dummyvar(Tii), 1); % Dummy var then cell
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% Build names
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namesii = strcat(T.Properties.VariableNames{ii}, '_', categoriesii);
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% Insert
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datastorage(idx:(idx+ncatii-1)) = dvii;
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namestorage(idx:(idx+ncatii-1)) = namesii;
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% Increment
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idx = idx+ncatii-1;
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else
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% Extract non categorical into current storage location
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datastorage{idx} = T{:,ii};
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namestorage(idx) = T.Properties.VariableNames(ii);
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end
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end
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% Build Tdummy with comma separated list expansion
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Tdummy = table(datastorage{:},'VariableNames',matlab.lang.makeValidName(namestorage));
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end
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