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» Learning classifiers from only positive and unlabeled data
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IJCV
2008
192views more  IJCV 2008»
13 years 7 months ago
Learning to Locate Informative Features for Visual Identification
Object identification (OID) is specialized recognition where the category is known (e.g. cars) and the algorithm recognizes an object's exact identity (e.g. Bob's BMW). ...
Andras Ferencz, Erik G. Learned-Miller, Jitendra M...
SDM
2010
SIAM
184views Data Mining» more  SDM 2010»
13 years 9 months ago
A Robust Decision Tree Algorithm for Imbalanced Data Sets
We propose a new decision tree algorithm, Class Confidence Proportion Decision Tree (CCPDT), which is robust and insensitive to class distribution and generates rules which are st...
Wei Liu, Sanjay Chawla, David A. Cieslak, Nitesh V...
HIS
2004
13 years 9 months ago
K-Ranked Covariance Based Missing Values Estimation for Microarray Data Classification
Microarray data often contains multiple missing genetic expression values that degrade the performance of statistical and machine learning algorithms. This paper presents a K rank...
Muhammad Shoaib B. Sehgal, Iqbal Gondal, Laurence ...
KDD
2009
ACM
269views Data Mining» more  KDD 2009»
14 years 8 months ago
Extracting discriminative concepts for domain adaptation in text mining
One common predictive modeling challenge occurs in text mining problems is that the training data and the operational (testing) data are drawn from different underlying distributi...
Bo Chen, Wai Lam, Ivor Tsang, Tak-Lam Wong
ICDE
2008
IEEE
165views Database» more  ICDE 2008»
14 years 8 months ago
Online Failure Forecast for Fault-Tolerant Data Stream Processing
In this paper, we present a new online failure forecast system to achieve predictive failure management for fault-tolerant data stream processing. Different from previous reactive ...
Xiaohui Gu, Spiros Papadimitriou, Philip S. Yu, Sh...