MLPRegressor

Regression with a multi-layer perceptron

Using FluCoMa to Make a Shared Instrument Exploring the Oboe with FluCoMa Levels of Translation Interface Design with FluCoMa Fleeting Networks Neural Network Parameters Neural Network Training Training and Testing Data Controlling a Synth using a Neural Network DataSet

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.

Pointer

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).