Conceptual Clustering Vs. Data Clustering
Conceptual clustering is obviously closely related to data clustering; however, in conceptual clustering it is not only the inherent structure of the data that drives cluster formation, but also the description language which is available to the learner. Thus, a statistically strong grouping in the data may fail to be extracted by the learner if the prevailing concept description language is incapable of describing that particular regularity. In most implementations, the description language has been limited to feature conjunction, although in COBWEB (see "COBWEB" below), the feature language is probabilistic.
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Famous quotes containing the words conceptual and/or data:
“We must not leap to the fatalistic conclusion that we are stuck with the conceptual scheme that we grew up in. We can change it, bit by bit, plank by plank, though meanwhile there is nothing to carry us along but the evolving conceptual scheme itself. The philosopher’s task was well compared by Neurath to that of a mariner who must rebuild his ship on the open sea.”
—Willard Van Orman Quine (b. 1908)
“This city is neither a jungle nor the moon.... In long shot: a cosmic smudge, a conglomerate of bleeding energies. Close up, it is a fairly legible printed circuit, a transistorized labyrinth of beastly tracks, a data bank for asthmatic voice-prints.”
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