Now showing items 1-4 of 4
VC-dimension of rule sets
(IEEE Computer Soc, 2014-08-24)
In this paper, we give and prove lower bounds of the VC-dimension of the rule set hypothesis class where the input features are binary or continuous. The VC-dimension of the rule set depends on the VC-dimension values of ...
Shallow parsing in Turkish
In this study, shallow parsing is applied on Turkish sentences. These sentences are used to train and test the per-formances of various learning algorithms with various features specified for shallow parsing in Turkish.
An incremental model selection algorithm based on cross-validation for finding the architecture of a Hidden Markov model on hand gesture data sets
In a multi-parameter learning problem, besides choosing the architecture of the learner, there is the problem of finding the optimal parameters to get maximum performance. When the number of parameters to be tuned increases, ...
Calculating the VC-dimension of decision trees
We propose an exhaustive search algorithm that calculates the VC-dimension of univariate decision trees with binary features. The VC-dimension of the univariate decision tree with binary features depends on (i) the ...