Vladimir Cherkassky and Filip Muller. Learning k-Svm Data Concepts, Theory, and Methods. John Wiley & SONS Inc., 1998. Home/Search Document Not in Database Summary Related Articles |
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Predicting Locations Using Map Similarity(PLUMS): A Framework .. - Chawla, Shekhar (2000) (Correct)
....with highest value of map similarity measure is chosen. This process is repeated and it ends when no neighbor has a higher value of map similarity measure, i.e. a local maxima has been found. Clearly, this search algorithm can be improved using a variety of ideas including gradient descent [4, 11] aad simulated annealing [32, 36] etc. A simple function family is the family of generalized linear models, e.g. logistic regression [22] with or without autocorrelation terms. Other interesting families include non linear fimctions. In the spatial statistics literature many functions have been ....
Vladimir Cherkassky and Filip Muller. Learning k-Svm Data Concepts, Theory, and Methods. John Wiley & SONS Inc., 1998.
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