Improvement of Performance in Multiclass Problems by Using Biclassification Based on Error-Correcting Output Code

نویسندگان

  • Young Bun Kim
  • Jung Hun Oh
  • Jean Gao
چکیده

Error-correcting output coding (ECOC) is a widely used multicategory classification algorithm that decomposes multiclass problems into a set of binary classification problems. In this paper, we propose a new method based on a bi-classification strategy, consisting of one-vs-one and ECOC classification. Also we introduce methods to improve a standard ECOC. The proposed method is compared to other algorithms by performing experiments with gene expression datasets.

برای دانلود 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

Error-Correcting Output Codes: A General Method for Improving Multiclass Inductive Learning Programs

Multiclass learning problems involve nding a deeni-tion for an unknown function f (x) whose range is a discrete set containing k > 2 values (i.e., k \classes"). The deenition is acquired by studying large collections of training examples of the form hx i ; f (x i)i. Existing approaches to this problem include (a) direct application of multiclass algorithms such as the decision-tree algorithms I...

متن کامل

IJESRT INTERNATIONAL JOURNA Empirical Study On Error Correcting Output Code Based On Multiclass

A common way to address a multi-class classification problem is to design a model that consists of hand picked binary classifiers and to combine them so as to solve the problem. Error such framework that deals with multi-class classification problems. Recent works in the ECOC domain has shown promising results demonstrating improved performance. Therefore, ECOC framework is a powerful tool to d...

متن کامل

Solving Multiclass Learning Problems via Error-Correcting Output Codes

Multiclass learning problems involve nding a de nition for an unknown function f(x) whose range is a discrete set containing k > 2 values (i.e., k \classes"). The de nition is acquired by studying collections of training examples of the form hxi; f(xi)i. Existing approaches to multiclass learning problems include direct application of multiclass algorithms such as the decision-tree algorithms C...

متن کامل

Solving Multiclass Learning Problems viaError - Correcting Output

Multiclass learning problems involve nding a deenition for an unknown function f (x) whose range is a discrete set containing k > 2 values (i.e., k \classes"). The deenition is acquired by studying collections of training examples of the form hx i ; f (x i)i. Existing approaches to multiclass learning problems include direct application of multiclass algorithms such as the decision-tree algorit...

متن کامل

On the Consistency of Output Code Based Learning Algorithms for Multiclass Learning Problems

A popular approach to solving multiclass learning problems is to reduce them to a set of binary classification problems through some output code matrix: the widely used one-vs-all and all-pairs methods, and the error-correcting output code methods of Dietterich and Bakiri (1995), can all be viewed as special cases of this approach. In this paper, we consider the question of statistical consiste...

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

برای دانلود 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

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2007