# MLPRegressor

Regression with a multi-layer perceptron

The MLPRegressor is a neural network that can be used to perform regression. In machine learning, regression can be thought of as a mapping from one space to another where each space can be any number of dimensions. “MLP” stands for multi-layer perceptron which is a type of neural network.

For more information on using this object, visit MLP Training, MLP Parameters, and Training-Testing Split.

By providing input and output data as DataSets, the neural network is trained using *supervised learning* to predict output data points based on input data points. See this YouTube tutorial that uses the MLPRegressor to control a synthesiser with 10 control parameters (as the output) using only 2 control parameters of an XY pad (as the input).