NIPS
2008
13 years 8 months ago
2008
Continuously-Adaptive Discretization for Message-Passing (CAD-MP) is a new message-passing algorithm for approximate inference. Most message-passing algorithms approximate continu...
NSDI
2008
13 years 9 months ago
2008
Discretization is used in click-based graphical passwords so that approximately correct entries can be accepted by the system. We show that the existing discretization scheme of B...
AUSAI
2003
Springer
13 years 11 months ago
2003
Springer
We investigate why discretization is effective in naive-Bayes learning. We prove a theorem that identifies particular conditions under which discretization will result in naiveBay...
ICDM
2007
IEEE
13 years 11 months ago
2007
IEEE
Data discretization is defined as a process of converting continuous data attribute values into a finite set of intervals with minimal loss of information. In this paper, we prove...
KDD
1997
ACM
13 years 11 months ago
1997
ACM
Many classification algorithms are designed to work with datasets that contain only discrete attributes. Discretization is the process of converting the continuous attributes of ...
GECCO
2004
Springer
14 years 24 days ago
2004
Springer
This paper proposes an experimental evaluation of various discretization schemes in three different evolutionary systems for inductive concept learning. The various discretization...
PKDD
2005
Springer
14 years 27 days ago
2005
Springer
This paper presents an unsupervised discretization method that performs density estimation for univariate data. The subintervals that the discretization produces can be used as the...
MLDM
2005
Springer
14 years 28 days ago
2005
Springer
Abstract. In supervised learning, discretization of the continuous explanatory attributes enhances the accuracy of decision tree induction algorithms and naive Bayes classifier. M...
AIPR
2005
IEEE
14 years 1 months ago
2005
IEEE
In this paper, we analyze the perturbation in the reconstructed optical absorption images, resulting from the discretization of the forward and inverse problems. We show that the ...
ECML
2007
Springer
14 years 1 months ago
2007
Springer
Abstract. The paper investigates modification of backpropagation algorithm, consisting of discretization of neural network weights after each training cycle. This modification, a...