The first session is on what is Cluster Analysis?
To understand what is cluster analysis, we should know first what is a cluster?
A cluster is actually a collection of data objects,
those objects are similar within the same cluster.
That means the objects are similar to one another within the same group.
And they are rather different, or they are dissimilar, or
unrelated, to the objects in other groups or in other clusters.
Okay, then cluster analysis which is also called clustering or
data segmentation, the essential is getting a set of tape data points.
The cluster analysis is to partition them into a set of clusters, or set of groups.
They are as similar as possible within the same group and
as far apart as possible among different groups.
Cluster analysis is unsupervised learning,
in the sense there's no predefined classes.
This is very different from classification which needs supervised learning or
needs to give in the class labors then you can construct the classification models.
There are many ways to use our apply cluster analysis,
essentially cluster analysis can either provide as a stand alone
tool to get insight into your data distribution like a summary.
Or you can serve, you can use it to serve as pre-processing step or
intermediate step for other algorithms,
like a classification or a prediction or like many other tasks,
including data mining and other applications.
Thank you.
[MUSIC]