Score Weighted

Rating Weighted

weighted saturation

Center weighted average

They're all weighted equally.

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Your eyesight will return in time.

He is weighted down with various cares.

We have a weighted mean over here.

What time do you usually return home?

I'll return it to you next time.

Finding the shortest path in a weighted, undirected connected graph took time m times the logarithm of n.

Finish your homework by the time they return.

Then the new mean, mu prime, is the weighted sum of the old means where mu is weighted by r squared and nu is weighted by sigma squared normalized by the sum of the weight factors.

You can see the curve is obviously heavily left weighted.

There is a definite time to return the book.

But every time I would return from my trips I'd return back to New York City.

He will have left here by the time you return.

It's the probability weighted sum of the squared distances from the mean.

That means that nu is weighted much, much larger than the mu.

The men won't return for seven hours, not until dinner time.

Remember, that is the weighted sum of the squared distances from the mean.

For the weighted average we get 2 times 10 plus 8 times 13.

Time is like a river it does not return to its source.

And in return, we just tried to kill them all the time.

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I will look in on you from time to time, and if you ever wish to return to Oz,

Well that's just the probability weighted sum of the values that this could take on.

That's all I'd like to say about shortest paths and weighted graphs in this unit.

I guess it will be a long time before I can return to Japan.

I thought I'd return the violin, and still have time to catch the train.

Carriage Return

SDL Return

Strobe return

Negative return.

If that happens, we'll return the return value.

You could have that situation where maybe the six sided is weighted a little bit more.

This would be a favor, which I would be pleased to return at any time.

We can't just return 0 all the time, because then our sum will be 0.

A safe answer is just to return false all the time, never do any optimization.

or n is equal to 1, return, return n!

The problem is that each timing is a different duration so it needs to be weighted differently.

Well, we would take a weighted average of these indices, or you could say a weighted average of the growth, you could do it either way, so let's do this either way to give you the same result.