Comment on "Support vector machine for classification based on fuzzy training data" by A.-B. Ji, J.-H. Pang, H.-J. Qiu [Expert Systems with Applications 37 (2010) 3495-3498]

نویسندگان

  • Yahya Forghani
  • Hadi Sadoghi Yazdi
  • Sohrab Effati
چکیده

This paper comments on the recently published work dealing with support vector machine for classification based on fuzzy data [Ji, A.-B., Pang, J.-H., & Qiu, H.-J. (2010). Support vector machine for classification based on fuzzy training data. Expert Systems with Applications 37(4), 3495–3498]. The authors have claimed that their proposed program is a classical convex quadratic program. But, we show that their proposed program is neither convex nor classical quadratic. Then, we propose a convex program by using the similar strategy proposed by Ji et al. (2010). 2012 Elsevier Ltd. All rights reserved.

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

Robustified distance based fuzzy membership function for support vector machine classification

Fuzzification of support vector machine has been utilized to deal with outlier and noise problem. This importance is achieved, by the means of fuzzy membership function, which is generally built based on the distance of the points to the class centroid. The focus of this research is twofold. Firstly, by taking the advantage of robust statistics in the fuzzy SVM, more emphasis on reducing the im...

متن کامل

Automatic Interpretation of UltraCam Imagery by Combination of Support Vector Machine and Knowledge-based Systems

With the development of digital sensors, an increasing number of high-resolution images are available. Interpretation of these images is not possible manually, which necessitates seeking for practical, fast and automatic solutions to solve the environmental and location-based management problems. The land cover classification using high-resolution imagery is a difficult process because of the c...

متن کامل

Fault diagnosis in a distillation column using a support vector machine based classifier

Fault diagnosis has always been an essential aspect of control system design. This is necessary due to the growing demand for increased performance and safety of industrial systems is discussed. Support vector machine classifier is a new technique based on statistical learning theory and is designed to reduce structural bias. Support vector machine classification in many applications in v...

متن کامل

A QUADRATIC MARGIN-BASED MODEL FOR WEIGHTING FUZZY CLASSIFICATION RULES INSPIRED BY SUPPORT VECTOR MACHINES

Recently, tuning the weights of the rules in Fuzzy Rule-Base Classification Systems is researched in order to improve the accuracy of classification. In this paper, a margin-based optimization model, inspired by Support Vector Machine classifiers, is proposed to compute these fuzzy rule weights. This approach not only  considers both accuracy and generalization criteria in a single objective fu...

متن کامل

PREDICTION OF SLOPE STABILITY STATE FOR CIRCULAR FAILURE: A HYBRID SUPPORT VECTOR MACHINE WITH HARMONY SEARCH ALGORITHM

The slope stability analysis is routinely performed by engineers to estimate the stability of river training works, road embankments, embankment dams, excavations and retaining walls. This paper presents a new approach to build a model for the prediction of slope stability state. The support vector machine (SVM) is a new machine learning method based on statistical learning theory, which can so...

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:
  • Expert Syst. Appl.

دوره 39  شماره 

صفحات  -

تاریخ انتشار 2012