KNN behavior with set-valued attributes

نویسندگان

  • Mabel González Castellanos
  • Yanet Rodríguez
  • Carlos Morell
چکیده

This paper addresses the problem of dealing with set-valued attributes in the lazy learning context. This type of attribute is present in various domains, yet the instance-based learning tools do not provide a representation for them. To solve this problem, we present a proposal for the treatment of the sets in the context of the k-NN algorithm through an extension to HEOM distance. Experiments using various data sets show the feasibility of this option.

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

Evolutionary fuzzy k-nearest neighbors algorithm using interval-valued fuzzy sets

One of the most known and effective methods in supervised classification is the K-Nearest Neighbors classifier. Several approaches have been proposed to enhance its precision, with the Fuzzy K-Nearest Neighbors (Fuzzy-kNN) classifier being among the most successful ones. However, despite its good behavior, Fuzzy-kNN lacks of a method for properly defining several mechanisms regarding the repres...

متن کامل

Some Results about Set-Valued Complementarity Problem

This paper is devoted to consider the notions of complementary problem (CP) and set-valued complementary problem (SVCP). The set-valued complementary problem is compared with the classical single-valued complementary problem. Also, the solution set of the set-valued complementary problem is characterized. Our results illustrated by some examples. This paper is devoted to co...

متن کامل

A Novel and Efficient KNN using Modified Apriori Algorithm

In the field of data mining, classification and association set rules are two of very important techniques to find out new patterns. K-nearest neighbor and apriori algorithm are most usable methods of classification and association set rules respectively. However, individually they face few challenges, such as, time utilization and inefficiency for very large databases. The current paper attemp...

متن کامل

Bioinformatics 2002 Bergen , Norway April 4 −

The paper contains the comparison between several class prediction methods (the K-Nearest Neighbour (KNN) algorithms and some variations of it) for classification of tumours using gene expression data. The KNN is a traditional classifier that uses a set of attributes for class prediction. Also are considered, the cases when these attributes (for KNN algorithm) are un-weighted (i.e. they all hav...

متن کامل

Hierarchical Bitmap Index: An Efficient and Scalable Indexing Technique for Set-Valued Attributes

Set-valued attributes are convenient to model complex objects occurring in the real world. Currently available database systems support the storage of set-valued attributes in relational tables but contain no primitives to query them efficiently. Queries involving set-valued attributes either perform full scans of the source data or make multiple passes over single-value indexes to reduce the n...

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 2010