BIRCH (data Clustering)
BIRCH (balanced iterative reducing and clustering using hierarchies) is an unsupervised data mining algorithm used to perform hierarchical clustering over particularly large data-sets. An advantage of Birch is its ability to incrementally and dynamically cluster incoming, multi-dimensional metric data points in an attempt to produce the best quality clustering for a given set of resources (memory and time constraints). In most cases, Birch only requires a single scan of the database. In addition, Birch is recognized as the, "first clustering algorithm proposed in the database area to handle 'noise' (data points that are not part of the underlying pattern) effectively".
Read more about BIRCH (data Clustering): Problem With Previous Methods, Advantages With BIRCH, BIRCH Clustering Algorithm, Awards, External Links
Famous quotes containing the word birch:
“The birch stripped of its bark, or the charred stump where a tree has been burned down to be made into a canoe,—these are the only traces of man, a fabulous wild man to us. On either side, the primeval forest stretches away uninterrupted to Canada, or to the “South Sea”; to the white man a drear and howling wilderness, but to the Indian a home, adapted to his nature, and cheerful as the smile of the Great Spirit.”
—Henry David Thoreau (1817–1862)