Linear Algebra Tools for Data Mining
Published May 1, 2012 · D. Simovici
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Abstract
Modules and Linear Spaces Matrices MATLAV Determinants Norms on Linear Spaces Inner Product Spaces Convexity Eigenvalues Similarity and Spectra Singular Values Graphs and Matrices Data Sample Matrices Least Squares Approximation and Data Mining Dimensionality Reduction Techniques The K-Means Clustering Algorithm Spectral Properties of Graphs and Spectral Clustering.
Study Snapshot
Key takeawayLinear Algebra tools can be used for data mining, including determining norms, inner product spaces, convexity, eigenvalues, similarity, and spectral clustering.
PopulationOlder adults (50-71 years)
Sample size24
MethodsObservational
OutcomesBody Mass Index projections
ResultsSocial networks mitigate obesity in older groups.