Konu "Decision trees" için MF - Bildiri Koleksiyonu | Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering listeleme
Toplam kayıt 12, listelenen: 1-12
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Budding trees
(IEEE Computer Soc, 2014-08-24)We propose a new decision tree model, named the budding tree, where a node can be both a leaf and an internal decision node. Each bud node starts as a leaf node, can then grow children, but then later on, if necessary, its ... -
Calculating the VC-dimension of decision trees
(IEEE, 2009)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 ... -
Feature extraction from discrete attributes
(IEEE, 2010)In many pattern recognition applications, first decision trees are used due to their simplicity and easily interpretable nature. In this paper, we extract new features by combining k discrete attributes, where for each ... -
Müşterilerin GSP analizi kullanarak kümelenmesi
(Institute of Electrical and Electronics Engineers Inc., 2018-07-05)Bu çalışma ile mevcut misafir ve rezervasyon verisi kullanılarak doğal öbeklenmeleri tespit ederek misafir davranışları tespit ettik. Ayrıca verilen hizmetleri ve satış stratejilerini bu davranışlara göre özelleştirdik. ... -
On the VC-dimension of univariate decision trees
(2012)In this paper, we give and prove lower bounds of the VC-dimension of the univariate decision tree hypothesis class. The VC-dimension of the univariate decision tree depends on the VC-dimension values of its subtrees and ... -
Regularizing soft decision trees
(Springer, 2013)Recently, we have proposed a new decision tree family called soft decision trees where a node chooses both its left and right children with different probabilities as given by a gating function, different from a hard ... -
Searching for the optimal ordering of classes in rule induction
(IEEE, 2012-11-15)Rule induction algorithms such as Ripper, solve a K > 2 class problem by converting it into a sequence of K - 1 two-class problems. As a usual heuristic, the classes are fed into the algorithm in the order of increasing ... -
Soft decision trees
(IEEE, 2012)We discuss a novel decision tree architecture with soft decisions at the internal nodes where we choose both children with probabilities given by a sigmoid gating function. Our algorithm is incremental where new nodes are ... -
Statistical tests using hinge/ε-sensitive loss
(Springer-Verlag, 2013)Statistical tests used in the literature to compare algorithms use the misclassification error which is based on the 0/1 loss and square loss for regression. Kernel-based, support vector machine classifiers (regressors) ... -
Tweet sentiment analysis for cryptocurrencies
(IEEE, 2021-10-13)Many traders believe in and use Twitter tweets to guide their daily cryptocurrency trading. In this project, we investigated the feasibility of automated sentiment analysis for cryptocurrencies. For the study, we targeted ... -
Univariate margin tree
(Springer, 2010)In many pattern recognition applications, first decision trees are used due to their simplicity and easily interpretable nature. In this paper, we propose a new decision tree learning algorithm called univariate margin ... -
VC-dimension of rule sets
(IEEE Computer Soc, 2014-12-04)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 ...