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SOM of SOMs. Presenter : Cheng-Feng Weng Authors : Tetsuo Furukawa 2009/07/09. NN.16 (2009). Outline. Motivation Objective Method Experiments Conclusion Comments. Motivation. The SOM provides a map of data vectors, but not a map of class distributions. Class confusion.
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SOM of SOMs Presenter : Cheng-Feng Weng Authors :Tetsuo Furukawa 2009/07/09 NN.16 (2009)
Outline • Motivation • Objective • Method • Experiments • Conclusion • Comments
Motivation • The SOM provides a map of data vectors, but not a map of class distributions. Class confusion
Motivation (cont.) • Manifoldcan be seen a class distributions. linear manifold viewpoint manifold
Objective • The paper is to propose a method of mapping class called SOMs that can represent the relationships between distributions. The manifold gradually changes shape. 15 classes
The SOMs • It is a hierarchical structure of a set of child SOMs and a single parent SOM. Manifold Class distributions Bottle up
The SOMs algorithm • There are J child SOMs and a parent SOM map. • Children and parent maps have own parameters. • Randomize parent SOM map, and use least qe map to replace child’s. • Class maps are estimated for each class dataset. • The BMMs are regarded as data vectors for parent map. • Update child’s weights by overwriting its BMM.
Conclusion • The essence of the algorithm is to generate a higher rank of data representation with class information as a clue, and the given datasets are modeled by fitting to a fiber bundle.
Comments • Advantage • From a class point of view • Inversed construction • Drawback • … • Application • Class manifold • LDA + SOM vs. SOM + LVQ