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Self-Organizing Maps, Principal Components and Non-negative ...

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<strong>Self</strong> <strong>Organizing</strong> <strong>Maps</strong><br />

<strong>Principal</strong> <strong>Components</strong>, Curves <strong>and</strong> Surfaces<br />

<strong>Non</strong>-<strong>negative</strong> Matrix Factorization<br />

<strong>Principal</strong> <strong>Components</strong><br />

<strong>Principal</strong> Curves<br />

Spectral Clustering<br />

N × N matrix of pairwise similarities sii ′ ≥ 0 between all<br />

observation pairs<br />

undirected similarity graph G = 〈V , E〉.<br />

The N vertices vi represent the observations.<br />

Pairs of vertices are connected by an edge if their similarity is<br />

positive.<br />

Karoline Geissler <strong>Self</strong>-<strong>Organizing</strong> <strong>Maps</strong>, <strong>Principal</strong> <strong>Components</strong> <strong>and</strong> <strong>Non</strong>-<strong>negative</strong> M

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