Filtreler

2007 - 200922010 - 20171
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Bölüm: Işık University, Faculty of Engineering, Department of Computer Engineering × Konu: Algorithm design and analysis ×

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Listeleniyor 1 - 3 / 3
  • Küçük Resim
    Yayın
    Calculating the VC-dimension of decision trees
    (IEEE, 2009) Aslan, Özlem; Yıldız, Olcay Taner; Alpaydın, Ahmet İbrahim Ethem
    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 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.
  • Küçük Resim
    Yayın
    A new approach for named entity recognition
    (IEEE, 2017) Ertopçu, Burak; Kanburoğlu, Ali Buğra; Topsakal, Ozan; Açıkgöz, Onur; Gürkan, Ali Tunca; Özenç, Berke; Çam, İlker; Avar, Begüm; Ercan, Gökhan; Yıldız, Olcay Taner
    Many sentences create certain impressions on people. These impressions help the reader to have an insight about the sentence via some entities. In NLP, this process corresponds to Named Entity Recognition (NER). NLP algorithms can trace a lot of entities in the sentence like person, location, date, time or money. One of the major problems in these operations are confusions about whether the word denotes the name of a person, a location or an organisation, or whether an integer stands for a date, time or money. In this study, we design a new model for NER algorithms. We train this model in our predefined dataset and compare the results with other models. In the end we get considerable outcomes in a dataset containing 1400 sentences.
  • Küçük Resim
    Yayın
    SPD (Static Priority with Deadline considerations) packet scheduling algorithm for achieving better QoS
    (IEEE, 2007) Dağ, Tamer
    Providing quality of service (QoS) to applications with different traffic characteristics based on their needs is an important research area for today's and tomorrow's high speed networks. Various techniques have been proposed to achieve good QoS for diverse application types. Among these techniques, packet scheduling algorithms decide on how to process packets at network nodes; however they have limited support for better QoS. In order to supply the various QoS requirements for different kinds of applications, new scheduling policies need to be developed and evaluated. This paper proposes a new kind of packet scheduling algorithm, Static Priority with Deadline Considerations (SPD), which integrates an important QoS parameter (the delay) into the classical static priority packet scheduling algorithm and analyses the packet losses by considering the two different components of losses; buffer overflows and deadline violations. The proposed algorithm not only reduces the complexity of the static priority algorithm by introducing degree sorting but also solves the starving problem and provides fairness to applications with different priorities.