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» An empirical comparison of supervised learning algorithms
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DATAMINE
2006
157views more  DATAMINE 2006»
14 years 11 months ago
Data Clustering with Partial Supervision
Clustering with partial supervision finds its application in situations where data is neither entirely nor accurately labeled. This paper discusses a semisupervised clustering algo...
Abdelhamid Bouchachia, Witold Pedrycz
NIPS
2003
15 years 1 months ago
Learning a Distance Metric from Relative Comparisons
This paper presents a method for learning a distance metric from relative comparison such as “A is closer to B than A is to C”. Taking a Support Vector Machine (SVM) approach,...
Matthew Schultz, Thorsten Joachims
TKDE
2008
112views more  TKDE 2008»
14 years 11 months ago
IDD: A Supervised Interval Distance-Based Method for Discretization
This paper introduces a new method for supervised discretization based on interval distances by using a novel concept of neighborhood in the target's space. The proposed metho...
Francisco J. Ruiz, Cecilio Angulo, Núria Ag...
ICML
2009
IEEE
16 years 16 days ago
Good learners for evil teachers
We consider a supervised machine learning scenario where labels are provided by a heterogeneous set of teachers, some of which are mediocre, incompetent, or perhaps even malicious...
Ofer Dekel, Ohad Shamir
PRICAI
2000
Springer
15 years 3 months ago
The Lumberjack Algorithm for Learning Linked Decision Forests
While the decision tree is an effective representation that has been used in many domains, a tree can often encode a concept inefficiently. This happens when the tree has to repres...
William T. B. Uther, Manuela M. Veloso