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» Boosted Optimization for Network Classification
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NIPS
2004
14 years 11 months ago
Optimal Aggregation of Classifiers and Boosting Maps in Functional Magnetic Resonance Imaging
We study a method of optimal data-driven aggregation of classifiers in a convex combination and establish tight upper bounds on its excess risk with respect to a convex loss funct...
Vladimir Koltchinskii, Manel Martínez-Ram&o...
SIGKDD
2008
150views more  SIGKDD 2008»
14 years 9 months ago
Learning to improve area-under-FROC for imbalanced medical data classification using an ensemble method
This paper presents our solution for KDD Cup 2008 competition that aims at optimizing the area under ROC for breast cancer detection. We exploited weighted-based classification me...
Hung-Yi Lo, Chun-Min Chang, Tsung-Hsien Chiang, Ch...
PAKDD
2000
ACM
161views Data Mining» more  PAKDD 2000»
15 years 1 months ago
Adaptive Boosting for Spatial Functions with Unstable Driving Attributes
Combining multiple global models (e.g. back-propagation based neural networks) is an effective technique for improving classification accuracy by reducing a variance through manipu...
Aleksandar Lazarevic, Tim Fiez, Zoran Obradovic
ICB
2007
Springer
214views Biometrics» more  ICB 2007»
15 years 1 months ago
Demographic Classification with Local Binary Patterns
LBP (Local Binary Pattern) as an image operator is used to extract LBPH (LBP histogram) features for texture description. In this paper, we present a novel method to use LBPH featu...
Zhiguang Yang, Haizhou Ai
ICANN
2007
Springer
15 years 3 months ago
Boosting Unsupervised Competitive Learning Ensembles
Topology preserving mappings are great tools for data visualization and inspection in large datasets. This research presents a combination of several topology preserving mapping mo...
Emilio Corchado, Bruno Baruque, Hujun Yin