Construction of nonlinear discrimination function based on the MDL criterion

نویسندگان

  • Manabu Sato
  • Mineichi Kudo
  • Jun Toyama
  • Masaru Shimbo
چکیده

Although a nonlinear discrimination function may be superior to linear or quadratic classiiers, it is diicult to construct such a function. In this paper, we propose a method to construct a nonlinear discrimination function using Legenedre polynomials. The selection of an optimal set of Legendre polynomials is determined by the MDL (Minimum Description Length) criterion. Results using many real data show the eeectiveness of this method.

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

ارزیابی روش‌های گروه‌بندی ژنوتیپ های کلزا با استفاده از تجزیه تابع تشخیص خطی فیشر

Discrimination function analysis is a method of multivariate analysis that can be used for determination of validity in cluster analysis. In this study, Fisher’s linear discrimination function analysis was used to evaluate the results from different methods of cluster analysis (i.e. different distance criteria, different cluster procedures, standardized and un-standardized data). Furthermore, H...

متن کامل

ارزیابی روش‌های گروه‌بندی ژنوتیپ های کلزا با استفاده از تجزیه تابع تشخیص خطی فیشر

Discrimination function analysis is a method of multivariate analysis that can be used for determination of validity in cluster analysis. In this study, Fisher’s linear discrimination function analysis was used to evaluate the results from different methods of cluster analysis (i.e. different distance criteria, different cluster procedures, standardized and un-standardized data). Furthermore, H...

متن کامل

Some Greedy Learning Algorithms for Sparse Regression and Classification with Mercer Kernels

We present some greedy learning algorithms for building sparse nonlinear regression and classification models from observational data using Mercer kernels. Our objective is to develop efficient numerical schemes for reducing the training and runtime complexities of kernel-based algorithms applied to large datasets. In the spirit of Natarajan’s greedy algorithm (Natarajan, 1995), we iteratively ...

متن کامل

Unsupervised speaker segmentation of broadcast news using MDL-based Gaussian model

This paper proposes an approach for unsupervised speaker segmentation and gender discrimination of broadcast news. In this paradigm, a speaker segmentation mechanism using MDL-based Gaussian model is firstly adopted to determine the speaker changes using mean and covariance of the Gaussian model. These speaker segments partitioned by speaker changes are smoothed and discriminated into male or f...

متن کامل

Simple and Efficient Algorithm for Improving the MDL Estimator of the Number of Sources

We propose a simple algorithm for improving the MDL (minimum description length) estimator of the number of sources of signals impinging on multiple sensors. The algorithm is based on the norms of vectors whose elements are the normalized and nonlinearly scaled eigenvalues of the received signal covariance matrix and the corresponding normalized indexes. Such norms are used to discriminate the ...

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:
  • Kybernetika

دوره 34  شماره 

صفحات  -

تاریخ انتشار 1998