Neural Net Clustering

Solve clustering problem using self-organizing map (SOM) networks

Description

The Neural Net Clustering app lets you create, visualize, and train self-organizing map networks to solve clustering problems.

Using this app, you can:

• Import data from file, the MATLAB^® workspace, or use one of the example data sets.

• Define and train a neural network.

• Analyze results using visualization plots, such as neighbor distance, weight planes, sample hits, and weight position.

• Generate MATLAB scripts to reproduce results and customize the training process.

• Generate functions suitable for deployment with MATLAB Compiler™ and MATLAB Coder™ tools, and export to Simulink^® for use with Simulink Coder.

Tip

To interactively build and visualize deep learning neural networks, use the Deep Network Designer app. For more information, see Get Started with Deep Network Designer.

×

Open the Neural Net Clustering App

• MATLAB Toolstrip: On the Apps tab, under Machine Learning and Deep Learning, click the app icon.

• MATLAB command prompt: Enter nctool.

Examples

• Cluster Data with a Self-Organizing Map

Algorithms

The Neural Net Clustering app provides a built-in training algorithm that you can use to train your neural network.

Training Algorithm	Description
Batch unsupervised weight and bias training	Train a network with unsupervised weight and bias learning rules with batch updates. The weights and biases are updated at the end of an entire pass through the input data. To implement this algorithm, the Neural Net Clustering app uses the trainbu function.