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Spectral—Wolfram Language Documentation

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• See Also
  • FindClusters
  • ClusterClassify
  • ClusteringComponents
  • ClusteringTree
  • Dendrogram
  • DimensionReduction
  • Methods
  • Agglomerate
  • GaussianMixture
  • JarvisPatrick
  • KMeans
  • KMedoids
  • MeanShift
  • NeighborhoodContraction
  • SpanningTree
• Tech Notes
  • Partitioning Data into Clusters

• Method for FindClusters, ClusterClassify and ClusteringComponents.
• Partitions data into clusters of similar elements using a "Spectral" method.

Find clusters of numbers using the "Spectral" method:

Find up to four clusters using the "Spectral" method:

Train the ClassifierFunction on a list of colors using the "Spectral" method:

Gather the elements by their class number:

Create and visualize noisy 2D moon-shaped training and test datasets:

Train a ClassifierFunction using the "Spectral" method; find and visualize clusters in the test set:

Perform cluster analysis of a computed tomography scan image using the "Spectral" method:

Create a ClassifierFunction from a list of images and classify examples using the "Spectral" method:

Find the cluster assignments and gather the elements by their corresponding clusters:

Find two clusters in data using Manhattan distance:

Define a set of two-dimensional data points, characterized by four somewhat nebulous clusters:

Plot clusters in data using Manhattan distance:

Find clusters by specifying the "NeighborhoodRadius" suboption:

Generate two moon-shaped datasets and visualize them:

Plot different clusterings of data using the "Spectral" method by varying the "NeighborhoodRadius":

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