FUZZY C-MEAN CLUSTERING USING DATA MINING leer epub gratis
FUZZY C-MEAN CLUSTERING USING DATA MINING de VIGNESH RAMAMOORTHY H
Ficha técnica
- FUZZY C-MEAN CLUSTERING USING DATA MINING
- VIGNESH RAMAMOORTHY H
- Idioma: INGLÉS
- Formatos: Pdf, ePub, MOBI, FB2
- ISBN: 9783748722182
- Editorial: BOOKRIX
Libros gratis en línea que puedes descargar FUZZY C-MEAN CLUSTERING USING DATA MINING 9783748722182 de VIGNESH RAMAMOORTHY H (Literatura española)
Overview
The goal of traditional clustering is to assign each data point to one and only one cluster. In contrast, fuzzy clustering assigns different degrees of membership to each point. The membership of a point is thus shared among various clusters. This creates the concept of fuzzy boundaries which differs from the traditional concept of well-defined boundaries. In hard clustering, data is divided into distinct clusters, where each data element belongs to exactly one cluster. In fuzzy clustering (also referred to as soft clustering), data elements can belong to more than one cluster, and associated with each element is a set of membership levels. These indicate the strength of the association between that data element and a particular cluster. Fuzzy clustering is a process of assigning these membership levels, and then using them to assign data elements to one or more clusters. This algorithm uses the FCM traditional algorithm to locate the centers of clusters for a bulk of data points. The potential of all data points is being calculated with respect to specified centers. The availability of dividing the data set into large number of clusters will slow the processing time and needs more memory size for the program. Hence traditional clustering should device the data to four clusters and each data point should be located in one specified cluster .Imprecision in data and information gathered from and about our environment is either statistical(e.g., the outcome of a coin toss is a matter of chance) or no statistical (e.g., "apply the brakes pretty soon"). Many algorithms can be implemented to develop clustering of data sets. Fuzzy C-mean clustering (FCM) is efficient and common algorithm. We are tuning this algorithm to get a solution for the rest of data point which omitted because of its farness from all clusters. To develop a high performance algorithm that sort and group data set in variable number of clusters to use this data in control and managing of those clusters.
PUBLICACIONES SIMILARES: {pdf download} Le Noeud de vipères site, DOWNLOAD [PDF] {EPUB} Legion versus Phalanx: The Epic Struggle for Infantry Supremacy in the Ancient World here, DOWNLOAD [PDF] {EPUB} Les enfants de D'Hara Tome 2 download link, DOWNLOADS The Invisible Life of Euridice Gusmao here, {pdf descargar} O ACHADO DO CASTRO read pdf, {pdf descargar} VICTORIA download link,