Nonparametric methods in DMML usually refers to the use of finite, possibly small data sets to search large spaces of functions. Large means, in particular, that the elements of the space cannot be indexed by a finite-dimensional parameter. Thus, large spaces are typically infinite-dimensional–and then some.
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© 2009 Springer-Verlag New York
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Clarke, B., Fokoué, E., Zhang, H.H. (2009). Local Smoothers. In: Principles and Theory for Data Mining and Machine Learning. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-0-387-98135-2_2
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DOI: https://doi.org/10.1007/978-0-387-98135-2_2
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