The self-organizing map (SOM) is an excellent tool in exploratory phase of data mining. It projects input space on prototypes of a low-dimensional regular ...
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Dec 9, 2013 · This paper extends the use of recently introduced Self-Organizing Time Map (SOTM) by pairing it with classical cluster analysis.
Aug 26, 2021 · We present a new DTW-based clustering method, called SOMTimeS (a Self-Organizing Map for TIME Series), that scales better and runs faster than other DTW-based ...
Oct 25, 2012 · You can basically do is two steps: build and train the som. And then, cluster the SOM, either on a static number of clusters or dynamic number of clusters.
Dec 15, 2021 · We can use self-organizing maps for clustering data, trained in an unsupervised way. Let's see how.
Sep 10, 2019 · Self Organizing Maps are a useful tool to cluster your data by building a map that takes potentially highly dimensional data and mapping it ...
This paper considers the problem of the clustering SOM using different aspects: partitioning, hierarchical and graph coloring based techniques.
The most important benefit of this procedure is that computational load decreases considerably, making it possible to cluster large data sets and to consider ...
Oct 20, 2023 · SOMTimeS is a self-organizing map for clustering and classifying time series data that uses DTW as a distance measure of similarity between time ...
May 21, 2021 · This example shows how to train a shallow neural network to cluster data using the Neural Net Clustering app.