A Study On High Dimensional Clustering By Using Clique
نویسندگان
چکیده
منابع مشابه
A Study on Clustering High Dimensional Data Using Hubness Phenomenon
Data mining is the non-trivial process of extracting information from the very large database. In recent years, data repository has a high dimensional data, which makes a complete search in most of the data mining problems leads computationally infeasible. To eradicate this problem clustering plays a vital role in handling low dimensional data and high dimensional data. Low dimensional data mak...
متن کاملa study on insurer solvency by panel data model: the case of iranian insurance market
the aim of this thesis is an approach for assessing insurer’s solvency for iranian insurance companies. we use of economic data with both time series and cross-sectional variation, thus by using the panel data model will survey the insurer solvency.
Evaluating a Clique Partitioning Problem Model for Clustering High-Dimensional Data Mining
This paper considers the problem of clustering high dimensional data as a clique partitioning problem. Data objects within a cluster have high degree of similarity. The similarity index values are first constructed into a graph as a clique partitioning problem which can be formulated into a form of unconstrained quadratic program model and then solved by a tabu search heuristic incorporating st...
متن کاملClustering Method Study on High-Dimensional Trading Data
Existing clustering algorithms are not designed specially for the features of trading data s and most clustering analyses lack scalability for large-scale transactions. Therefore, a rapid and scalable clustering algorithm using little space is proposed by us, to effectively process high-dimensional trading data without setting parameters manually. The improved method introduces weighted coverag...
متن کاملClustering High Dimensional Data Using SVM
The Web contains massive amount of documents from across the globe to the point where it has become impossible to classify them manually. This project’s goal is to find a new method for clustering documents that are as close to humans’ classification as possible and at the same time to reduce the size of the documents. This project uses a combination of Latent Semantic Indexing (LSI) with Singu...
متن کاملذخیره 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 Computer Science and Informatics
سال: 2011
ISSN: 2231-5292
DOI: 10.47893/ijcsi.2011.1019