In this third and final part of episode
2 we're going to continue where we left
off. In the two previous episodes where I
have shown you from installation of the
WEKA software to pre-processing the
data set and model construction using
the decision tree algorithm C4.5. In this video, I will show you
how to interpret the decision rules
obtained from the decision tree model so
without further ado let's get started. So
let's have a look at the tree, what does
it actually look like? You can
right-click on this label here and then
find visualize tree and then this is the
tree this is the decision tree created
by the J48 or the C4.5 algorithm.
The first one represents the root node and 
the rectangle represents the leaf node. And so
these represents the subsequent
branching out of the variables. So let's
start from the root node here so the
first variable is petal width and if the
petal width has a value of less than -0.784457
then we can classify it as being Iris setosa and in parentheses,
50 of these are using this rule. So if
the petal width has a value greater than
0.656917 then we can say that it is an Iris
virginica and 46 of these have been
correctly classified and 1 have been
misclassified. And so we can do the same with the branching out of node
as well. So this means that in order to be
classified as Iris versicolor here, the
petal width needs to be in the range of
-0.78 and 0.65. This is the first
variable and the second variable needs
to have petal length value of less than
0.64 to be an Iris versicolor. And so
if we move on to the subsequent branch
here, the petal length has a value
greater than 0.64 and the petal
width has a value less than
0.39, then we can say that it is an Iris
virginica. However, if the petal width has
a value of greater than 0.39, then we can
see that it is an Iris versicolor. So this
visual tree will allow us to come up with the 
visualization of the if and then rules of
the decision tree that have been created.
And we can see that 96% accuracy was
afforded by the tree. So, very useful and
that's about it. So, congratulations you
have just built your first prediction
model. And in the future videos, we're
going to cover some more algorithms and
other interesting data mining software
as well. So until next time, I'm Chanin Nantasenamat on the Data Professor
channel. And if you haven't subscribed
yet, please consider subscribing and
clicking on the notification bell so
that you will be notified on the next
video. So I'll see you in the next one!
