# Functions by Category

Local Model Toolbox

## Contents

- Local Model Network Training
- Common Functions
- Algorithms
- Common Classes

## Local Model Network Training

- `LMNTrain` - Train and compare local model networks

## Common Functions

- `train` - Train a local model

Plot Functions

- `plotCorrelation` - Plot the correlation between model output and training, validation and test data

- `plotLossFunction` - Plot the global and penalty lossfunctions

- `plotModel` - Plot the model output of a trained model

- `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

- `lolimot` - Local Linear Model Tree

- `hilomot` - Hirachic Local Model Tree

## Common Classes

- `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` - 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.