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» Semi-Supervised Learning with Trees
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ICML
2003
IEEE
14 years 9 months ago
Tractable Bayesian Learning of Tree Augmented Naive Bayes Models
Bayesian classifiers such as Naive Bayes or Tree Augmented Naive Bayes (TAN) have shown excellent performance given their simplicity and heavy underlying independence assumptions....
Jesús Cerquides, Ramon López de M&aa...
JMLR
2006
112views more  JMLR 2006»
13 years 8 months ago
Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting
We develop kernels for measuring the similarity between relational instances using background knowledge expressed in first-order logic. The method allows us to bridge the gap betw...
Andrea Passerini, Paolo Frasconi, Luc De Raedt
TJS
2010
182views more  TJS 2010»
13 years 6 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
PAMI
2011
13 years 3 months ago
Greedy Learning of Binary Latent Trees
—Inferring latent structures from observations helps to model and possibly also understand underlying data generating processes. A rich class of latent structures are the latent ...
Stefan Harmeling, Christopher K. I. Williams
ICDM
2006
IEEE
119views Data Mining» more  ICDM 2006»
14 years 2 months ago
Fast On-line Kernel Learning for Trees
Kernel methods have been shown to be very effective for applications requiring the modeling of structured objects. However kernels for structures usually are too computational dem...
Fabio Aiolli, Giovanni Da San Martino, Alessandro ...