eBooks mean - Bücher suchen

Ben Lev Mean Goose

Belletristik
Englisch
198 Wörter
Keine Altersempfehlung
228
0

Their was a mean goose that everybody hated and then she learned a lesson

Stichwörter: Goose, fable, mean, children, bedtime story

Kostenlos

Ben Lev Mean Goose

Belletristik
Englisch
171 Wörter
Keine Altersempfehlung
379
0

WHat a mean goose gets

Kostenlos

Hunter Parrett Bullying, Hurtful Or Mean?

Ratgeber
Englisch
3082 Wörter
Ab 12 Jahren
375
0

Bullying, Hurtful Or Mean? Talks about Why people bully, how to deal with bullies, different types of bullying, [mehr]

Stichwörter: Bullying

3,49 US$

Erika Ilene Peña Mean Boy, With a Love.

Lyrik und Poesie
Englisch
192 Wörter
Keine Altersempfehlung
278
0

It's a poem , about a guy that had a "Mean" type of love. I named it 'Mean [mehr]

Kostenlos

Destini Robinson Cupid's Mean

Lyrik und Poesie
Englisch
123 Wörter
Keine Altersempfehlung
303
1

Kostenlos

VIGNESH RAMAMOORTHY H Fuzzy C-mean Clustering using Data Mining

Technik
Englisch
19875 Wörter
Ab 10 Jahren
75
0

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. [mehr]

5,49 US$