| Neural Net Clustering | Cluster data by training a self-organizing maps network |
selforgmap | Self-organizing map |
train | Train shallow neural network |
plotsomhits | Plot self-organizing map sample hits |
plotsomnc | Plot self-organizing map neighbor connections |
plotsomnd | Plot self-organizing map neighbor distances |
plotsomplanes | Plot self-organizing map weight planes |
plotsompos | Plot self-organizing map weight positions |
plotsomtop | Plot self-organizing map topology |
genFunction | Generate MATLAB function for simulating shallow neural network |
Cluster Data with a Self-Organizing Map
Group data by similarity using the Neural Network Clustering App or command-line functions.
Deploy Shallow Neural Network Functions
Simulate and deploy trained shallow neural networks using MATLAB® tools.
Deploy Training of Shallow Neural Networks
Learn how to deploy training of shallow neural networks.
This example illustrates how a self-organizing map neural network can cluster iris flowers into classes topologically, providing insight into the types of flowers and a useful tool for further analysis.
This example demonstrates looking for patterns in gene expression profiles in baker's yeast using neural networks.
One-Dimensional Self-organizing Map
Neurons in a 2-D layer learn to represent different regions of the input space where input vectors occur.
Two-Dimensional Self-organizing Map
As in one-dimensional problems, this self-organizing map will learn to represent different regions of the input space where input vectors occur.
Cluster with Self-Organizing Map Neural Network
Use self-organizing feature maps (SOFM) to classify input vectors according to how they are grouped in the input space.