𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Risk estimation and risk prediction using machine-learning methods

✍ Scribed by Kruppa, Jochen; Ziegler, Andreas; König, Inke R.

Book ID
118785802
Publisher
Springer
Year
2012
Tongue
English
Weight
863 KB
Volume
131
Category
Article
ISSN
0340-6717

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✍ Kerkyacharian Gérard; Picard Dominique 📂 Article 📅 1997 🏛 Elsevier Science 🌐 English ⚖ 656 KB

We prove here that when estimating a density, using a kernel or a linear wavelet estimate, one can choose the smoothing parameter such that the limit when n tends to infinity of n2/3EIIF -fn I1~ may be arbitrarily small for every density having a square integrable derivative. This choice consists in