Applications of regularized least squares to pattern classification

نویسندگان

چکیده

برای دانلود رایگان 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

Applications of regularized least squares to pattern classification

We survey a number of recent results concerning the behaviour of algorithms for learning classifiers based on the solution of a regularized least-squares problem. c © 2007 Elsevier B.V. All rights reserved.

متن کامل

Regularized Least-Squares Classification

We consider the solution of binary classification problems via Tikhonov regularization in a Reproducing Kernel Hilbert Space using the square loss, and denote the resulting algorithm Regularized Least-Squares Classification (RLSC). We sketch the historical developments that led to this algorithm, and demonstrate empirically that its performance is equivalent to that of the well-known Support Ve...

متن کامل

Applications of Regularized Least Squares to Classification Problems

We present a survey of recent results concerning the theoretical and empirical performance of algorithms for learning regularized least-squares classifiers. The behavior of these family of learning algorithms is analyzed in both the statistical and the worst-case (individual sequence) data-generating models. 1 Regularized Least-Squares for Classification In the pattern classification problem, s...

متن کامل

Discriminatively regularized least-squares classification

Over the past decades, regularization theory is widely applied in various areas of machine learning to derive a large family of novel algorithms. Traditionally, regularization focuses on smoothing only, and does not fully utilize the underlying discriminative knowledge which is vital for classification. In this paper, we propose a novel regularization algorithm in the least-squares sense, calle...

متن کامل

Regularized Least Squares Piecewise Multi-classification Machine

This paper presents a Tikhonov regularization based piecewise classification model for multi-category discrimination of sets or objects. The proposed model includes a linear classification and nonlinear kernel classification model formulation. Advantages of the regularized multi-classification formulations include its ability to express a multi-class problem as a single and unconstrained optimi...

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: Theoretical Computer Science

سال: 2007

ISSN: 0304-3975

DOI: 10.1016/j.tcs.2007.03.053