Download Dataset Shift In M...

Masashi Sugiyama

Format: Hardcover

Language: English

Pages: 248

Publisher: The MIT Press (December 12, 2008)


Format: PDF / Kindle / ePub

Size: 5.2 MB

Downloadable formats: PDF

Dataset shift is a typical challenge in predictive modeling that happens whilst the joint distribution of inputs and outputs differs among education and try out levels. Covariate shift, a specific case of dataset shift, happens whilst purely the enter distribution alterations. Dataset shift is found in such a lot useful functions, for purposes starting from the prejudice brought by way of experimental layout to the irreproducibility of the checking out stipulations at education time. (An instance is -email junk mail filtering, which can fail to acknowledge junk mail that differs in shape from the unsolicited mail the automated clear out has been equipped on.) regardless of this, and regardless of the eye given to the it appears related difficulties of semi-supervised studying and energetic studying, dataset shift has acquired particularly little realization within the desktop studying neighborhood till lately. This quantity bargains an summary of present efforts to house dataset and covariate shift. The chapters provide a mathematical and philosophical creation to the matter, position dataset shift in courting to move studying, transduction, neighborhood studying, energetic studying, and semi-supervised studying, offer theoretical perspectives of dataset and covariate shift (including determination theoretic and Bayesian perspectives), and current algorithms for covariate shift. members [cut for catalog if necessary]Shai Ben-David, Steffen Bickel, Karsten Borgwardt, Michael Brückner, David Corfield, Amir Globerson, Arthur Gretton, Lars Kai Hansen, Matthias Hein, Jiayuan Huang, Choon Hui Teo, Takafumi Kanamori, Klaus-Robert Müller, Sam Roweis, Neil Rubens, Tobias Scheffer, Marcel Schmittfull, Bernhard Schölkopf Hidetoshi Shimodaira, Alex Smola, Amos Storkey, Masashi Sugiyama

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