Hello there.
Welcome back to in this lecture we will be learning about flustering.
So what flustering really does is it tries to group or cluster our different set of objects together
based on their properties.
Suppose you have some kind of data where are that or where there are many objects.
So what clustering algorithm really do is it tries to group all those sort of data into different clusters
based on their similar properties.
So interesting there are no classes defined.
And it tries to group a set of objects and find whether there is some relationship between any objects
or not.
Suppose this is your original and cluster data when we apply clustering in it with a group or clusters
same data together just like this so we can do this in power as well.
So let's jump back to power to see how this works.
So for this we will take our Jard
We will dig it up in the Detail section we will take our customer name and we will do that clustering
for sales data sets and the quantity order
that there go.
So let me show you how this thing really works.
I will remove from I will remove the customer name.
Now you can see how easy it is to do that clustering here in our bay.
So I think that customer name in the D-Del. sections Let's see which thing really works.
So I was I've already taken part the code which is our products here.
So what I'm really trying to do is I'm trying to find where I can get the most number of datapoints.
So I think the protocol is much better than this.
So this particular here is kind of an outlier which I can remove.
So now let's do the glistering so to to do clustering who are in power.
You can see the three Lipsius up here.
So the scatter chart when you click here on this you can see the option of automatically finding clusters
just simply click on here and then you will do that a pop up will appear.
So it will ask you about the name the description and how many clusters you have to form.
So suppose I have to form let's say three clusters of my data so I will type in three.
OK.
It will automatically create a measure to find to give me that cluster of my products.
So there you go.
This is my cluster one cluster This is my second this is my third cluster.
So based on the properties similar properties because the plus tertiary black that having some maximum
number of cells and the quantities are all so much.
So they are one cluster.
Another question here is in the middle which are driving average number of cells and the quantity order
is also say almost similar and the lowest cells have been all up in that cluster.
So this much easier as it is here possible to define clusters.
So now what you can do is we can remove this outlier which is kind of getting our chart in our genes.
It is not really helping much to visualize or chart like this.
So what we can do here is I can remove this one so the protocol is as 1:42 to do with the visual level
filters I can remove this one.
I would select all.
I would just search for that particular and I removed it.
There you go.
So now you can see how weird it looks like that this particular clustering chart for all the three different
cluster we can create any number of clusters like five or 10.
As part our need to design our clustering is done in power B.A another way of doing clustering here
if I were we I is using the custom visuals.
So this was done by our own scatter chart.
Another way is to use any kind of custom modules from marketplace so I have imported some of my some
custom visuals from a market place like flustering westering with outlier.
These are similar clustering jars so you can just simply put them up here and therefore and your values
like for the x and y axis I will put my boat sails and the quantity order based on the and my data up
on labels will be my products so this will take some time to load this particular graph but this will
be done.
You will see that the automatic clustering will be done here using this particular custom module.
There you go.
So what it has done here is that as part of the cluster we are in the red and there are some outliers
in the black.
I will change this particular chart which does normal clustering chart
my data point labor will be brought up.
So there are two charts.
Just have one difference that this particular target form.
Give us some outliers as well.
And this will just form the clustering.
So when we know that you can see all the clustering and once that list things done you can do apply
some formatting here from the formatting.
Ben
so these are some of the ways of doing clustering here in power be clustering really helps us to analyze
our data and we have to group them based on certain properties.
So we don't have to write any code or something like that we in power.
All you have to do is just select clustering feature to automatically form clusters using our eyes inby
algorithms that will automatically create those clusters for you.
So that's a pretty easy way of doing things up here.
As I've told you this particular customers will take some amount of time to do that clustering submission
but once done here is this is how it will look like it has cluster under there type of three perspired
the border guards are having a little bit different.
Not much because here in the x axis I have big quantity ordered as you can see in the vibe there are
a number of things while in our other chart in the x axis that is says and the quantity are the reason
why X is so there are just because of that there is some difference in the mission of our visuals.
But this is all clustering is done.
So in the next lecture we will be taking a look about the regression technique here in power.
So that's all about clustering up here and we'll meet in the next lecture.
Thank you.