<--- Back to Details
First PageDocument Content
Machine learning / Statistical classification / Actuarial science / Formal sciences / Statistical theory / Risk / Linear classifier / Pattern recognition / Statistics / Expected value / Loss function / Value at risk
Date: 2015-02-02 08:46:12
Machine learning
Statistical classification
Actuarial science
Formal sciences
Statistical theory
Risk
Linear classifier
Pattern recognition
Statistics
Expected value
Loss function
Value at risk

Microsoft Word - IBSNew_Trends_in_iTECH-final

Add to Reading List

Source URL: foibg.com

Download Document from Source Website

File Size: 790,24 KB

Share Document on Facebook

Similar Documents

Advanced Methods in Statistical Classification SS 2013 Type Schedule / Room V3 Block course 01 April to 19th April Mo-Fr 1000 –

DocID: 1uQKO - View Document

Statistical and Computational Challenges in Networks and Cybersecurity Community Detection and Classification in Hierarchical Stochastic Blockmodels Carey E. Priebe

DocID: 1u9u0 - View Document

McRank: Learning to Rank Using Multiple Classification and Gradient Boosting Ping Li ∗ Dept. of Statistical Science Cornell University

DocID: 1tgDg - View Document

On the Statistical Consistency of Algorithms for Binary Classification under Class Imbalance Aditya Krishna Menon University of California, San Diego, La Jolla CA 92093, USA

DocID: 1sKKN - View Document

SEMINAR ON STATISTICAL MAPPING This seminar, held in two sessions on Monday and Wednesday afternoons, dealt with statistical mapping, map generalization and classification. Papers were presented by JEAN-CLAUDE MULLER, R

DocID: 1szhk - View Document