Combinatorial Methods in Density Estimation
Dis 2012 · Springer Science & Business Media
I-Ebook
209
Amakhasi
reportIzilinganiso nezibuyekezo aziqinisekisiwe Funda Kabanzi
Mayelana nale ebook
Density estimation has evolved enormously since the days of bar plots and histograms, but researchers and users are still struggling with the problem of the selection of the bin widths. This text explores a new paradigm for the data-based or automatic selection of the free parameters of density estimates in general so that the expected error is within a given constant multiple of the best possible error. The paradigm can be used in nearly all density estimates and for most model selection problems, both parametric and nonparametric. It is the first book on this topic. The text is intended for first-year graduate students in statistics and learning theory, and offers a host of opportunities for further research and thesis topics. Each chapter corresponds roughly to one lecture, and is supplemented with many classroom exercises. A one year course in probability theory at the level of Feller's Volume 1 should be more than adequate preparation. Gabor Lugosi is Professor at Universitat Pompeu Fabra in Barcelona, and Luc Debroye is Professor at McGill University in Montreal. In 1996, the authors, together with Lászlo Györfi, published the successful text, A Probabilistic Theory of Pattern Recognition with Springer-Verlag. Both authors have made many contributions in the area of nonparametric estimation.
Nikeza le ebook isilinganiso
Sitshele ukuthi ucabangani.
Ulwazi lokufunda
Amasmathifoni namathebulethi
Faka uhlelo lokusebenza lwe-Google Play Amabhuku lwe-Android ne-iPad/iPhone. Livunyelaniswa ngokuzenzakalela ne-akhawunti yakho liphinde likuvumele ukuthi ufunde uxhunywe ku-inthanethi noma ungaxhunyiwe noma ngabe ukuphi.
Amakhompyutha aphathekayo namakhompyutha
Ungalalela ama-audiobook athengwe ku-Google Play usebenzisa isiphequluli sewebhu sekhompuyutha yakho.
Ama-eReaders namanye amadivayisi
Ukuze ufunde kumadivayisi e-e-ink afana ne-Kobo eReaders, uzodinga ukudawuniloda ifayela futhi ulidlulisele kudivayisi yakho. Landela imiyalelo Yesikhungo Sosizo eningiliziwe ukuze udlulise amafayela kuma-eReader asekelwayo.
