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      • Department of Electrical and Electronics Engineering
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      A tree-based solution to nonlinear regression problem

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      Author(s)
      Demir, Oğuzhan
      Neyshabouri, Mohammadreza Mohaghegh
      Delibalta, İ.
      Kozat, Süleyman Serdar
      Date
      2016
      Source Title
      Proceedings of the IEEE 24th Signal Processing and Communications Applications Conference, SIU 2016
      Publisher
      IEEE
      Pages
      1233 - 1236
      Language
      Turkish
      Type
      Conference Paper
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      Abstract
      In this paper, we offer and examine a new algorithm for sequential nonlinear regression problem. In this architecture, we use piecewise adaptive linear functions to find the nonlinear regression model sequentially. For more accurate and faster convergence, we combine a large class of piecewise linear functions. These piecewise linear functions are constructed by composing different adaptive linear functions, which are represented by the nodes of a lexicographical tree. With this tree structure, computational complexity of the algorithm is significantly reduced. To show the performance of the proposed algorithm, we present a simulation which is performed by using a well-known real data set.
      Keywords
      On-line learning
      Classification
      Computational efficiency
      Permalink
      http://hdl.handle.net/11693/37702
      Published Version (Please cite this version)
      http://dx.doi.org/10.1109/SIU.2016.7495969
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      • Department of Electrical and Electronics Engineering 4011
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