abstract - Kroombats

hundredcarriageΛογισμικό & κατασκευή λογ/κού

3 Νοε 2013 (πριν από 3 χρόνια και 8 μήνες)

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ABSTRACT


Cluster analysis is a more primitive technique in that no assumptions are made concerning
the number of groups or the group structure. Groupings are done on the basis of similarities or
distances (dissimilarities). The inputs required are
similarity measures or data from which
similarities can be computed.


Cluster analysis of a tool for exploring the structure of data. The core of cluster
analysis is clustering. The process of grouping objects into clusters such that the objects from the
s
ame cluster are similar and objects from different clusters are dissimilar. Objects can be described
in terms of measurements(example, attributes ,features) or by relationships with other
objects(example, pairwise distance, similarity). Unlike classificati
on, clustering does not require
assumptions about category labels that tag objects with prior identifiers. Therefore, clustering is an
unsupervised learning technique versus classification, which belongs to supervised learning.




The need to structure an
d learn from the vigorously growing amounts of
data has been a driving force for making clustering a highly active research area. Humans are not
able to easily discover knowledge from the glut of information in databases without the use of
summarization t
echniques. Basic statistics(such as mean, variance) or histograms can provide an
initial feel for the data. However, more intricate relationships among the objects, among the
features, and between both can be discovered through cluster analysis.


Hardware
Requirements:



Processor


:

Pentium or Above



RAM



:

1GB



Hard Disk


:

20GB

3.
4

Software Requirements
:



Operating System

:

Windows/Linux



Front End


:

Java (Swing)



Back End


:

Any Database