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» Evaluating learning algorithms and classifiers
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102
Voted
KDD
2004
ACM
196views Data Mining» more  KDD 2004»
16 years 2 days ago
Adversarial classification
Essentially all data mining algorithms assume that the datagenerating process is independent of the data miner's activities. However, in many domains, including spam detectio...
Nilesh N. Dalvi, Pedro Domingos, Mausam, Sumit K. ...
BMVC
2010
14 years 9 months ago
StyP-Boost: A Bilinear Boosting Algorithm for Learning Style-Parameterized Classifiers
We introduce a novel bilinear boosting algorithm, which extends the multi-class boosting framework of JointBoost to optimize a bilinear objective function. This allows style param...
Jonathan Warrell, Philip H. S. Torr, Simon Prince
102
Voted
IJDMB
2007
110views more  IJDMB 2007»
14 years 11 months ago
Transductive learning with EM algorithm to classify proteins based on phylogenetic profiles
: Phylogenetic profiles of proteins  strings of ones and zeros encoding respectively the presence and absence of proteins in a group of genomes  have recently been used to id...
Roger A. Craig, Li Liao
IDEAL
2004
Springer
15 years 5 months ago
Learning to Classify Biomedical Terms Through Literature Mining and Genetic Algorithms.
We present an approach to classification of biomedical terms based on the information acquired automatically from the corpus of relevant literature. The learning phase consists of...
Irena Spasic, Goran Nenadic, Sophia Ananiadou
KDD
2003
ACM
180views Data Mining» more  KDD 2003»
16 years 2 days ago
Classifying large data sets using SVMs with hierarchical clusters
Support vector machines (SVMs) have been promising methods for classification and regression analysis because of their solid mathematical foundations which convey several salient ...
Hwanjo Yu, Jiong Yang, Jiawei Han