Protein fold recognition based on error correcting output codes and SVM.

نویسندگان

  • Yuehui Chen
  • Qing Chen
  • Feng Chen
  • Yaou Zhao
چکیده

A new approach based on the implementation of support vector machine (SVM) with the error correcting output codes (ECOC) is presented for recognition of multi-class protein folds. The experimental show that the proposed method can improve prediction accuracy by 4%-10% on two datasets containing 27 SCOP folds.

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

An approach to fault detection and correction in design of systems using of Turbo ‎codes‎

We present an approach to design of fault tolerant computing systems. In this paper, a technique is employed that enable the combination of several codes, in order to obtain flexibility in the design of error correcting codes. Code combining techniques are very effective, which one of these codes are turbo codes. The Algorithm-based fault tolerance techniques that to detect errors rely on the c...

متن کامل

Epileptic seizure detection based on The Limited Penetrable visibility graph algorithm and graph properties

Introduction: Epileptic seizure detection is a key step for both researchers and epilepsy specialists for epilepsy assessment due to the non-stationariness and chaos in the electroencephalogram (EEG) signals. Current research is directed toward the development of an efficient method for epilepsy or seizure detection based the limited penetrable visibility graph (LPVG) algorith...

متن کامل

Using diversity measures for generating error-correcting output codes in classifier ensembles

Error-correcting output codes (ECOC) are used to design diverse classifier ensembles. Diversity within ECOC is traditionally measured by Hamming distance. Here we argue that this measure is insufficient for assessing the quality of code for the purposes of building accurate ensembles. We propose to use diversity measures from the literature on classifier ensembles and suggest an evolutionary al...

متن کامل

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

Separability of ternary codes for sparse designs of error-correcting output codes

Error-correcting output codes (ECOC) represent a successful framework to deal with multi-class categorization problems based on combining binary classifiers. With the extension of the binary ECOC to the ternary ECOC framework, ECOC designs have been proposed in order to better adapt to distributions of the data. In order to decode ternary matrices, recent works redefined many decoding strategie...

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:
  • Protein and peptide letters

دوره 15 5  شماره 

صفحات  -

تاریخ انتشار 2008