Design und Management komplexer technischer Prozesse und Systeme mit Methoden der Computational Intelligence Evolutionary Support Vector Machines and their Application for Classification

نویسندگان

  • Ruxandra Stoean
  • Mike Preuss
  • Catalin Stoean
  • D. Dumitrescu
چکیده

We propose a novel learning technique for classification as result of the hybridization between support vector machines and evolutionary algorithms. Evolutionary support vector machines consider the classification task as in support vector machines but use evolutionary algorithms to solve the optimization problem of determining the decision function. They can acquire the coefficients of the separating hyperplane, which is often not possible within classical techniques. More important, ESVMs obtain the coefficients directly from the evolutionary algorithm and can refer them at any point during a run. The concept is furthermore extended to handle large amounts of data, a problem frequently occurring e.g. in spam mail detection, one of our test cases. Evolutionary support vector machines are validated on this and three other real-world classification tasks; obtained results show the promise of this new technique.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Design und Management komplexer technischer Prozesse und Systeme mit Methoden der Computational Intelligence TAKEOVER TIME IN PARALLEL POPULATIONS WITH MIGRATION

The term takeover time regarding selection methods used in evolutionary algorithms denotes the (expected) number of iterations of the selection method until the entire population consists of copies of the best individual, provided that the initial population consists of a single copy of the best individual whereas the remaining individuals are worse. Here, this notion is extended to parallel su...

متن کامل

Design und Management komplexer technischer Prozesse und Systeme mit Methoden der Computational Intelligence Pareto Set and EMOA Bahavior for Simple Multimodal Multiobjective Functions

Recent research on evolutionary multiobjective optimization has mainly focused on Pareto-fronts. However, we state that proper behavior of the utilized algorithms in decision/search space is necessary for obtaining good results if multimodal objective functions are concerned. Therefore, it makes sense to observe the development of Pareto-sets as well. We do so on a simple, configurable problem,...

متن کامل

Design und Management komplexer technischer Prozesse und Systeme mit Methoden der Computational Intelligence Pareto Set and EMOA Behavior for Simple Multimodal Multiobjective Functions

Recent research on evolutionary multiobjective optimization has mainly focused on Pareto-fronts. However, we state that proper behavior of the utilized algorithms in decision/search space is necessary for obtaining good results if multimodal objective functions are concerned. Therefore, it makes sense to observe the development of Pareto-sets as well. We do so on a simple, configurable problem,...

متن کامل

Design und Management komplexer technischer Prozesse und Systeme mit Methoden der Computational Intelligence Evolutionary Optimization of Dynamic Multiobjective Functions

Many real-world problems show both multiobjective as well as dynamic characteristics. In order to use multiobjective evolutionary optimization algorithms (MOEA) efficiently, a systematic analysis of the behavior of these algorithms in dynamic environments is necessary. Dynamic fitness functions can be classified into problems with moving Pareto fronts and Pareto sets having varying speed, shape...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2006