Support Vector Machines using Multi Objective Linear Programming

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

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

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Linear programming support vector machines

Based on the analysis of the conclusions in the statistical learning theory, especially the VC dimension of linear functions, linear programming support vector machines (or SVMs) are presented including linear programming linear and nonlinear SVMs. In linear programming SVMs, in order to improve the speed of the training time, the bound of the VC dimension is loosened properly. Simulation resul...

متن کامل

Multi-Objective Optimization of Support Vector Machines

Designing supervised learning systems is in general a multi-objective optimization problem. It requires finding appropriate trade-offs between several objectives, for example between model complexity and accuracy or sensitivity and specificity. We consider the adaptation of kernel and regularization parameters of support vector machines (SVMs) by means of multi-objective evolutionary optimizati...

متن کامل

Semiparametric Support Vector and Linear Programming Machines

Semiparametric models are useful tools in the case where domain knowledge exists about the function to be estimated or emphasis is put onto understandability of the model. We extend two learning algorithms Support Vector machines and Linear Programming machines to this case and give experimental results for SV machines.

متن کامل

STAGE-DISCHARGE MODELING USING SUPPORT VECTOR MACHINES

Establishment of rating curves are often required by the hydrologists for flow estimates in the streams, rivers etc. Measurement of discharge in a river is a time-consuming, expensive, and difficult process and the conventional approach of regression analysis of stage-discharge relation does not provide encouraging results especially during the floods. P

متن کامل

Deep Learning using Linear Support Vector Machines

Recently, fully-connected and convolutional neural networks have been trained to achieve state-of-the-art performance on a wide variety of tasks such as speech recognition, image classification, natural language processing, and bioinformatics. For classification tasks, most of these “deep learning” models employ the softmax activation function for prediction and minimize cross-entropy loss. In ...

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

ژورنال

عنوان ژورنال: Transactions of the Institute of Systems, Control and Information Engineers

سال: 2003

ISSN: 1342-5668,2185-811X

DOI: 10.5687/iscie.16.70