3 sonuçlar
Arama Sonuçları
Listeleniyor 1 - 3 / 3
Yayın Calculating the VC-dimension of decision trees(IEEE, 2009) Aslan, Özlem; Yıldız, Olcay Taner; Alpaydın, Ahmet İbrahim EthemWe 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 VC-dimension values of the left and right subtrees, (ii) the number of inputs, and (iii) the number of nodes in the tree. From a training set of example trees whose VC-dimensions are calculated by exhaustive search, we fit a general regressor to estimate the VC-dimension of any binary tree. These VC-dimension estimates are then used to get VC-generalization bounds for complexity control using SRM in decision trees, i.e., pruning. Our simulation results shows that SRM-pruning using the estimated VC-dimensions finds trees that are as accurate as those pruned using cross-validation.Yayın Budding trees(IEEE Computer Soc, 2014-08-24) İrsoy, Ozan; Yıldız, Olcay Taner; Alpaydın, Ahmet İbrahim EthemWe 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 children can be pruned. This contrasts with traditional tree construction algorithms that only grows the tree during the training phase, and prunes it in a separate pruning phase. We use a soft tree architecture and show that the tree and its parameters can be trained using gradient-descent. Our experimental results on regression, binary classification, and multi-class classification data sets indicate that our newly proposed model has better performance than traditional trees in terms of accuracy while inducing trees of comparable size.Yayın Investigation and prediction of surface integrity induced by milling of hot forged and heat treated AA7075(Motto, 2024-11-03) Tok, Görkem; Dinçer, Ammar Tarık; Kuzu, Ali Taner; Bakkal, Mustafa; Saklakoğlu, İ. EtemThis study examines the influence of cutting parameters on surface integrity, focusing on residual stress and surface roughness, in hot-forged and T6 heat-treated AA7075 components post-milling. Using the Taguchi L9 DOE method, orthogonal cutting milling experiments were performed, with residual stress measured via nondestructive X-ray diffraction (XRD). The analysis indicated that lower cutting speeds reduce residual stress, with down milling causing compressive and up milling causing tensile stresses. A proposed model showed a significant correlation between cutting force and residual stress—higher cutting forces increased residual stress. Surface roughness assessment revealed that feed rate greatly impacts residual stress, with lower feed rates reducing roughness. These insights will aid in developing a regression model for predicting outcomes in future experiments, enhancing the understanding and control of surface integrity in milling AA7075 components.
