So this is the dataset that we are going to use to build that classification.
The data set is exactly similar to the one that we used for building out regression tree.
These are the same variables.
Only thing is that in the end.
Last thing we were predicting the value of collection to, we had the information about all these variables
and we were trying to predict the value of collection in this dataset.
We already know that.
How much?
A movie has collected at the box office.
Now we want to predict whether that particular movie is going to win a star like Oscar or not.
So this particular award, will any of these movies win or Nortman besides the data?
And this lady was.
Again, this data is for, I wondered, six movies for these 506 movies.
We have the data whether they've won or whether they did not win the static Oscar using this data.
We will train our model.
We will spread the data into two parts.
One part will be used to pay non-moral.
The other part will be used to check its performance.
And once we have created this model, we can use that model to predict whether any particular movie
is going to win a static Oscar or not by putting the value of all these other variables into our model.