Design of nearest neighbor classifiers: multi-objective approach

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

Design of nearest neighbor classifiers: multi-objective approach

The goal of designing optimal nearest neighbor classifiers is to maximize classification accuracy while minimizing the sizes of both reference and feature sets. A usual way is to adaptively weight the three objectives as an objective function and then use a single-objective optimization method for achieving this goal. This paper proposes a multi-objective approach to cope with the weight tuning...

متن کامل

Design of Nearest Neighbor Classifiers Using an Intelligent Multi-objective Evolutionary Algorithm

The goal of designing optimal nearest neighbor classifiers is to maximize classification accuracy while minimizing the sizes of both reference and feature sets. A usual way is to adaptively weight the three objectives as an objective function and then use a single-objective optimization method for achieving this goal. This paper proposes a multi-objective approach to cope with the weight tuning...

متن کامل

Nearest Neighbor Classifiers

The 1-N-N classifier is one of the oldest methods known. The idea is extremely simple: to classify X find its closest neighbor among the training points (call it X ,) and assign to X the label of X .

متن کامل

Validation of nearest neighbor classifiers

We develop a probabilistic bound on the error rate of the nearest neighbor classiier formed from a set of labelled examples. The bound is computed using only the examples in the set. A subset of the examples is used as a validation set to bound the error rate of the classiier formed from the remaining examples. Then a bound is computed for the diierence in error rates between the original class...

متن کامل

Coevolution of Nearest Neighbor Classifiers

This paper presents experiments of Nearest Neighbor (NN) classifier design using different evolutionary computation methods. Through multi-objective and co-evolution techniques, it combines genetic algorithms and genetic programming to both select NN prototypes and design a neighborhood proximity measure, in order to produce a more efficient and robust classifier. The proposed approach is compa...

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: International Journal of Approximate Reasoning

سال: 2005

ISSN: 0888-613X

DOI: 10.1016/j.ijar.2004.11.009