To Enhance A-KNN Clustering Algorithm for Improving Software Architecture

نویسنده

  • Sandeep Singh
چکیده

Software Architecture is important factor for the development of complex and big software system. Software Architecture Decomposition is an important part in software design. Software clustering is used to cluster functions of similar type in one cluster and other are in other cluster. Kmean is the base of the clustering but it has some limitations. Many clustering methods are used for decomposition the software architecture. A-KNN cluster method is more efficient than others methods but some functions are highly coupled then cluster technique does not find out correct distance. So that need to enhancement in Euclidian distance formula based on normalization. In this paper, an enhancement has proposed in the Euclidean distance formula which has increased the cluster quality. When the cluster quality will be increase then cluster the highly coupled function properly and improve the software architecture and A-KNN will be generate the best results than previous method. Keyword: Architecture, A-KNN, Clustering, Decomposition.

برای دانلود رایگان 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

A Proposal to Enhance A-KNN Clustering Method

To maintain the quality of software and to better understand it, software architecture is decomposed. Software decomposition is done by various clustering methods. Each method provides different results of clustering on datasets. This paper presents the review of various clustering methods with A-KNN method in terms of efficiency and accuracy. It also proposes the way to enhance AKNN clustering...

متن کامل

A Novel Scheme for Improving Accuracy of KNN Classification Algorithm Based on the New Weighting Technique and Stepwise Feature Selection

K nearest neighbor algorithm is one of the most frequently used techniques in data mining for its integrity and performance. Though the KNN algorithm is highly effective in many cases, it has some essential deficiencies, which affects the classification accuracy of the algorithm. First, the effectiveness of the algorithm is affected by redundant and irrelevant features. Furthermore, this algori...

متن کامل

A partition-based algorithm for clustering large-scale software systems

Clustering techniques are used to extract the structure of software for understanding, maintaining, and refactoring. In the literature, most of the proposed approaches for software clustering are divided into hierarchical algorithms and search-based techniques. In the former, clustering is a process of merging (splitting) similar (non-similar) clusters. These techniques suffered from the drawba...

متن کامل

kEFCM: kNN-Based Dynamic Evolving Fuzzy Clustering Method

Despite the recent emergence of research, creating an evolving fuzzy clustering method that intelligently copes with huge amount of data streams in the present high-speed networks involves a lot of difficulties. Several efforts have been devoted to enhance traditional clustering techniques into on-line evolving fuzzy able to learn and develop continuously. In line with these efforts, we propose...

متن کامل

Fault Detection Using the Clustering-kNN Rule for Gas Sensor Arrays

The k-nearest neighbour (kNN) rule, which naturally handles the possible non-linearity of data, is introduced to solve the fault detection problem of gas sensor arrays. In traditional fault detection methods based on the kNN rule, the detection process of each new test sample involves all samples in the entire training sample set. Therefore, these methods can be computation intensive in monitor...

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

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2015