Browsing by Author "Güvenir, H. Altay"

Now showing items 1-11 of 11

    • An application of genetic programming to the 4-Op problem using map-trees 

      Aytekin, Tevfik; Korkmaz, E. Erkan; Güvenir, H. Altay (Springer, Berlin, Heidelberg, 1995)
      In Genetic programming (GP) applications the programs are expressed as parse trees. A node of a parse tree is an element either from the function-set or terminal-set, and an element of a terminal set can be used in a parse ...

    • ARG: A tool for automatic report generation 

      Karakaya, K. Murat; Güvenir, H. Altay (Aves Yayıncılık, 2004)
      The expansion of on-line text with the rapid growth of the Internet imposes utilizing Data Mining techniques to reveal the information embedded in these documents. Therefore text classification and text summarization are ...

    • Classification by voting feature intervals 

      Demiröz, Gülşen; Güvenir, H. Altay (Springer, 1997-04)
      A new classification algorithm called VFI (for Voting Feature Intervals) is proposed. A concept is represented by a set of feature intervals on each feature dimension separately. Each feature participates in the classification ...

    • A classification learning algorithm robust to irrelevant features 

      Güvenir, H. Altay (Springer, 1998-09)
      Presence of irrelevant features is a fact of life in many realworld applications of classification learning. Although nearest-neighbor classification algorithms have emerged as a promising approach to machine learning tasks ...

    • Distributed artificial intelligence in engineering design 

      Polat, Faruk; Güvenir, H. Altay (ASME, 1992)
      Distributed Artificial Intelligence (DAI) research is concerned with solving problems using both AI techniques and distributed processing. DAI techniques can be used to solve many complex problems such as engineering design ...

    • An eager regression method based on best feature projections 

      Aydın, Tolga; Güvenir, H. Altay (Springer, Berlin, Heidelberg, 2001)
      This paper describes a machine learning method, called Regression by Selecting Best Feature Projections (RSBFP). In the training phase, RSBFP projects the training data on each feature dimension and aims to find the ...

    • Learning translation templates for closely related languages 

      Altıntaş, Kemal; Güvenir, H. Altay (Springer, Berlin, Heidelberg, 2003)
      Many researchers have worked on example-based machine translation and different techniques have been investigated in the area. In literature, a method of using translation templates learned from bilingual example pairs was ...

    • Maximizing benefit of classifications using feature intervals 

      İkizler, Nazlı; Güvenir, H. Altay (Springer, Berlin, Heidelberg, 2003)
      There is a great need for classification methods that can properly handle asymmetric cost and benefit constraints of classifications. In this study, we aim to emphasize the importance of classification benefits by means ...

    • Preface 

      Roth-Berghofer, T. R.; Göker, M. H.; Güvenir, H. Altay (Springer, Berlin, Heidelberg, 2006)

    • A privacy-preserving solution for the bipartite ranking problem 

      Faramarzi, Noushin Salek; Ayday, Erman; Güvenir, H. Altay (IEEE, 2016-12)
      In this paper, we propose an efficient solution for the privacy-preserving of a bipartite ranking algorithm. The bipartite ranking problem can be considered as finding a function that ranks positive instances (in a dataset) ...

    • Supervised machine learning algorithm for arrhythmia analysis 

      Güvenir, H. Altay; Acar, Burak; Demiröz, Gülşen; Çekin, A. (IEEE, 1997)
      A new machine learning algorithm for the diagnosis of cardiac arrhythmia from standard 12 lead ECG recordings is presented. The algorithm is called VFI5 for Voting Feature Intervals. VFI5 is a supervised and inductive ...