EECS 800 Research Seminar Mining Biological Data. Instructor: Luke Huan Fall, 2006. Overview. A quick review of PCA Graph mining in microarray analysis Graph indexing. Data Matrix. The data matrix: where is a column vector is the column mean of. Projection.
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Instructor: Luke Huan
where is a column vector
is the column mean of
where is a unit column vector
Where is the covariance matrix
To find λ that maximizes V subject to
Let k be a Lagrange multiplier
Therefore λ is an eigenvector of Σ.
Chose the engenvector with the largest eigenvalue
Let G be a frequent graph and X be the set
of edges which can be added to G such that
G U e (e ε X) is connected and frequent.
Graph G U X is the maximal graph that can be
extended for the vertices belong to G.
G U X
Let V(G) be the vertex set of a graph and E(G) its edge set. Graphs G and H are isomorphic iff there is a bijection f: V(G) →V(H) such that uv ε E(G) if and only if f(u)f(v) ε E(G).
For example, in the graph of benzene, vertexes labeled with “C” correspond with carbon atoms. Vertexes with “H” correspond with hydrogen atoms.
Nodes and edges with different class labels are not considered interchangeable.
In other words:
Thus, similarity is application dependent.