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ADMA
2006
Springer
121views Data Mining» more  ADMA 2006»
14 years 3 months ago
A New Polynomial Time Algorithm for Bayesian Network Structure Learning
We propose a new algorithm called SCD for learning the structure of a Bayesian network. The algorithm is a kind of constraintbased algorithm. By taking advantage of variable orderi...
Sanghack Lee, Jihoon Yang, Sungyong Park
AI
1998
Springer
14 years 1 months ago
Sequential Instance-Based Learning
This paper presents and evaluates sequential instance-based learning (SIBL), an approach to action selection based upon data gleaned from prior problem solving experiences. SIBL le...
Susan L. Epstein, Jenngang Shih
METRICS
1997
IEEE
14 years 1 months ago
Assessing Feedback Of Measurement Data: Relating Schlumberger Rps Practice To Learning Theory
Schlumberger RPS successfully applies software measurement to support their software development projects. It is proposed that the success of their measurement practices is mainly...
Rini van Solingen, Egon Berghout, Erik Kooiman
IJCNLP
2005
Springer
14 years 2 months ago
A Machine Learning Approach to Sentence Ordering for Multidocument Summarization and Its Evaluation
Ordering information is a difficult but a important task for natural language generation applications. A wrong order of information not only makes it difficult to understand, but a...
Danushka Bollegala, Naoaki Okazaki, Mitsuru Ishizu...
UAI
1998
13 years 10 months ago
A Multivariate Discretization Method for Learning Bayesian Networks from Mixed Data
In this paper we address the problem of discretization in the context of learning Bayesian networks (BNs) from data containing both continuous and discrete variables. We describe ...
Stefano Monti, Gregory F. Cooper