%% Functions by Category
% Local Model Toolbox
% 
%
%% Local Model Network Training
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% * <LMNTrain_help.html |LMNTrain|> - Train and compare local model
% networks
%
%% Common Functions
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% * <train_help.html |train|> - Train a local model
%
%
% * <calculateModelOutput_help.html |calculateModelOutput|> - Train a local model
%
% *Plot Functions*
%
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% * <plotCorrelation_help.html |plotCorrelation|> - Plot the correlation between
% model output and training, validation and test data
% 
% * <plotLossFunction_help.html |plotLossFunction|> - Plot the global and
% penalty lossfunctions
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% * <plotModel_help.html |plotModel|> - Plot the model output of a trained
% model
%
% * <plotPartition_help.html |plotPartition|> - Plot the validity funciton
% values of the premise input space (z-regressors) of the neuro-fuzzy model
% (1- or 2-dimensional plot only)
%
%% Algorithms
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% * <lolimot_help.html |lolimot|> - Local Linear Model Tree
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% * <hilomot_help.html |hilomot|> - Hirachic Local Model Tree
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%% Common Classes
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% * <dataSet_help.html |dataSet|> - This class generates a dataSet object,
% which stores measured data. Beneath the ability to store data, there are
% methods to normalize/denormalize the data and to set a name for the whole
% dataSet as well as for the various in- and outputs.
%
% * <dataSetInfo_help.html |dataSetInfo|> - This class generates creates an
% object, that contains information about a dataSet object, such as the
% dataSet description and the description of all in- and outputs.
