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ESEM
2008
ACM
13 years 10 months ago
A hybrid faulty module prediction using association rule mining and logistic regression analysis
This paper proposes a fault-prone module prediction method that combines association rule mining with logistic regression analysis. In the proposed method, we focus on three key m...
Yasutaka Kamei, Akito Monden, Shuuji Morisaki, Ken...
IMC
2010
ACM
13 years 6 months ago
On economic heavy hitters: shapley value analysis of 95th-percentile pricing
Cost control for the Internet access providers (AP) influences not only the nominal speeds offered to the customers, but also other, more controversial, policies related to traffi...
Rade Stanojevic, Nikolaos Laoutaris, Pablo Rodrigu...
ICCV
2003
IEEE
14 years 10 months ago
Learning a Locality Preserving Subspace for Visual Recognition
Previous works have demonstrated that the face recognition performance can be improved significantly in low dimensional linear subspaces. Conventionally, principal component analy...
Xiaofei He, Shuicheng Yan, Yuxiao Hu, HongJiang Zh...
ICASSP
2011
IEEE
13 years 12 days ago
Improved speaker recognition when using i-vectors from multiple speech sources
The concept of speaker recognition using i-vectors was recently introduced offering state-of-the-art performance. An i-vector is a compact representation of a speaker’s utteranc...
Mitchell McLaren, David A. van Leeuwen
ESEM
2007
ACM
14 years 17 days ago
The Effects of Over and Under Sampling on Fault-prone Module Detection
The goal of this paper is to improve the prediction performance of fault-prone module prediction models (fault-proneness models) by employing over/under sampling methods, which ar...
Yasutaka Kamei, Akito Monden, Shinsuke Matsumoto, ...