October 2017
Beginner to intermediate
572 pages
26h 1m
English
ISOMAP is one of the approaches for manifold learning, which generalizes linear framework to nonlinear data structures. Similar to MDS, ISOMAP creates a visual presentation of similarities or dissimilarities (distance) of a number of objects. However, as the data is structured in a nonlinear format, the Euclidian distance measure of MDS is replaced by the geodesic distance of a data manifold in ISOMAP. In this recipe, we will illustrate how to perform a nonlinear dimension reduction with ISOMAP.
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