Left margin

Right margin

Top margin

Bottom margin

Customize gaps and margins

But this is the difference between operating income and EBlT.

And so EBlT factors that in.

EBlT divided by assets.

While operating profit, you start at the top line and you go down.

I'm going to make the text of our submit button bigger.

I know that look like a very strange word.

You might immediately say, if I took net income so let's remember EBlT is just an acronym for Earnings Before

So in general if you want to know what I think is the best

And so this distance is called the margin of the support vector machine and this gives the SVM a certain robustness, because it tries to separate the data with as a large a margin as possible.

Configure layout, names and margins

I'm going to sketch a

What are your operating costs? What are the basic fixed and variable costs of the business?

This option allows customization of Gaps and Margins.

So that's what EBlT is right here.

There is no free market for oil.

It affects your sales model. Are you going to hire direct sales? When do you hire them?

Then whatever this generates is actually non operating income.

It also has very high cost implications.

let's actually talk about this for a second.

You're making good margins.

So I hope that gives some intuition about how this support vector machine functions as a large margin classifier that tries to separate the data with a large margin, technically this picture of this view is true only when the parameter C is very large, which is a useful way to think about support vector machines.

And our art titles are going to be bold, and they're going to be 20 pixels tall the font.

This is a pretty profitable business, more profitable than most.

Because it tells you either how much operating profit is being generated from here, or it could tell you how much EBlT.

EBlT in this case would be the operating profit plus this investment income.

And we add back the interest, at least in this example, we get to an operating profit number.

Now, the SVM is actually sligthly more sophisticated than this large margin view might suggest.

Change paragraph margins, text flow, borders, bullets, numbering etc.

That is, trying to separate the positive and negative examples with as big a margin as possible.

But in general if you take EBlT and you take out the non operating income, you get back to operating profits.

Sometimes people talk about support vector machines, as large margin classifiers, in this video I'd

If he had one example then it seems as if to separate data with a large margin, maybe I'll end up learning a decision boundary like that, right? that is the magenta line and it's really not clear that based on the single outlier based on a single example and it's really not clear that it's actually a good idea to change my decision boundary from the black one over to the magenta one.

And what type of a return can they get?

But then the last one, if I have time to go over, we'll call it EBlT.

No, what happened to us, Chris, is that power, it's priced off the margin.

And so this picture of a large margin classifier that's really, that's really the picture that gives better intuition only for the case of when the regulations parameter C is very large, and just to remind you this corresponds

like this, maybe we'll choose that decision boundary that separate the positive and negative examples on large margin.

So the support vector machine is sometimes also called a large margin classifier and this is actually a consequence of the optimization problem we wrote down on the previous slide.

And so their operating profit, the amount of pre tax income, but you know, we're not considering financing either, so this is their operating profit or their EBlT.

It draws your text bold, a little larger with a little margin around it, and that's it.