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TJS
2010
182views more  TJS 2010»
13 years 8 months ago
A novel unsupervised classification approach for network anomaly detection by k-Means clustering and ID3 decision tree learning
This paper presents a novel host-based combinatorial method based on k-Means clustering and ID3 decision tree learning algorithms for unsupervised classification of anomalous and ...
Yasser Yasami, Saadat Pour Mozaffari
ECCV
2008
Springer
14 years 11 months ago
Keypoint Signatures for Fast Learning and Recognition
Abstract. Statistical learning techniques have been used to dramatically speed-up keypoint matching by training a classifier to recognize a specific set of keypoints. However, the ...
Michael Calonder, Vincent Lepetit, Pascal Fua
KDD
2003
ACM
150views Data Mining» more  KDD 2003»
14 years 10 months ago
Learning relational probability trees
Classification trees are widely used in the machine learning and data mining communities for modeling propositional data. Recent work has extended this basic paradigm to probabili...
Jennifer Neville, David Jensen, Lisa Friedland, Mi...
ECML
2007
Springer
14 years 3 months ago
Decision Tree Instability and Active Learning
Decision tree learning algorithms produce accurate models that can be interpreted by domain experts. However, these algorithms are known to be unstable – they can produce drastic...
Kenneth Dwyer, Robert Holte
EMNLP
2007
13 years 11 months ago
A Comparative Evaluation of Deep and Shallow Approaches to the Automatic Detection of Common Grammatical Errors
This paper compares a deep and a shallow processing approach to the problem of classifying a sentence as grammatically wellformed or ill-formed. The deep processing approach uses ...
Joachim Wagner, Jennifer Foster, Josef van Genabit...