1454 search results - page 29 / 291 » Learning with cost intervals |
AAAI
1997
14 years 11 months ago
1997
The absolute loss is the absolute difference between the desired and predicted outcome. I demonstrateworst-case upper bounds on the absolute loss for the perceptron algorithm and ...
ILP
2000
Springer
15 years 1 months ago
2000
Springer
A method for learning multivariate time series classifiers by inductive logic programming is presented. Two types of background predicate that are suited for this task are introduc...
CORR
2010
Springer
14 years 8 months ago
2010
Springer
We consider linear models for stochastic dynamics. To any such model can be associated a network (namely a directed graph) describing which degrees of freedom interact under the d...
ECML
2005
Springer
15 years 3 months ago
2005
Springer
We study cost-sensitive learning of decision trees that incorporate both test costs and misclassification costs. In particular, we first propose a lazy decision tree learning that ...
ICML
2004
IEEE
15 years 10 months ago
2004
IEEE
We propose a simple, novel and yet effective method for building and testing decision trees that minimizes the sum of the misclassification and test costs. More specifically, we f...