Personalized mode transductive spanning SVM classification tree

نویسندگان

  • Shaoning Pang
  • Tao Ban
  • Youki Kadobayashi
  • Nikola K. Kasabov
چکیده

Article history: Received 28 February 2009 Received in revised form 27 October 2010 Accepted 1 January 2011 Available online 14 January 2011

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

Spanning SVM Tree for Personalized Transductive Learning

Personalized Transductive Learning (PTL) builds a unique local model for classification of each test sample and therefore is practically neighborhood dependant. While existing PTL methods usually define the neighborhood by a predefined (dis)similarity measure, in this paper we introduce a new concept of knowledgeable neighborhood and a transductive SVM classification tree (t-SVMT) for PTL. The ...

متن کامل

Guest editorial : Thematic issue on ‘ Adaptive Soft Computing

Personalized Transductive Learning (PTL) builds a unique local model for classification of each test sample and therefore is practically neighborhood dependant, i.e. a specific model is built in a subspace spanned by a set of samples adjacent to the test sample. While existing PTL methods usually define the neighborhood by a predefined (dis)similarity measure, in this paper we introduce a new c...

متن کامل

Spectral-spatial classification of hyperspectral images by combining hierarchical and marker-based Minimum Spanning Forest algorithms

Many researches have demonstrated that the spatial information can play an important role in the classification of hyperspectral imagery. This study proposes a modified spectral–spatial classification approach for improving the spectral–spatial classification of hyperspectral images. In the proposed method ten spatial/texture features, using mean, standard deviation, contrast, homogeneity, corr...

متن کامل

Efficiency Comparison of Unstable Transductive and Inductive Conformal Classifiers

In the conformal prediction literature, it appears axiomatic that transductive conformal classifiers possess a higher predictive efficiency than inductive conformal classifiers, however, this depends on whether or not the nonconformity function tends to overfit misclassified test examples. With the conformal prediction framework’s increasing popularity, it thus becomes necessary to clarify the ...

متن کامل

Learning with Progressive Transductive Support Vector Machine

Support vector machine (SVM) is a new learning method developed in recent years based on the foundations of statistical learning theory. By taking a transductive approach instead of an inductive one in support vector classifiers, the working set can be used as an additional source of information about margins. Compared with traditional inductive support vector machines, transductive support vec...

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:
  • Inf. Sci.

دوره 181  شماره 

صفحات  -

تاریخ انتشار 2011