So that it minimizes the squared error.

所以它最小化平方误差。

In the cost function, the squared error for the second example is also 0 squared.

在成本函数中，第二个示例的平方误差也是 0 平方。

And then we're going to square that error.

然后我们要纠正这个错误。

So this is the squared error of the line.

所以这是直线的平方误差。

And what we want to do is minimize this squared error from each of these points to the line.

我们要做的是最小化从每个点到直线的平方误差。

So let me define the squared error against this line as being equal to the sum of these squared errors.

因此，让我将这条线的平方误差定义为等于这些平方误差的总和。

Sometimes, it's called the squared error.

有时，它称为平方误差。

And we want the squared errors between each of the points of the line.

我们想要直线上每个点之间的平方误差。

Let me call this the squared error from the average.

让我将其称为平均值的平方误差。

So if we find the m and the b values that satisfy the system of equations, we have minimized the squared error.

所以如果我们找到满足方程组的 m 和 b 值，我们就已经最小化了平方误差。

We have the squared error of the line.

我们有直线的平方误差。

The total variation in y, which is the squared error from the mean of the y's.

y 的总变差，它是 y 的均值的平方误差。

If the squared error of the line is really small what does that mean?

如果线的平方误差真的很小，那意味着什么？

Our goal is to find the m and the b, which would define an actual line, that minimize the squared error.

我们的目标是找到 m 和 b，它们将定义一条实际直线， 使平方误差最小化。

If the squared error of the line is small, it tells us that the line is a good fit.

如果直线的平方误差很小，则说明直线拟合得很好。

So are squared error versus our line, our total squared error, we just computed to be 2.74.

平方误差与我们的线，我们的总平方误差，我们刚刚计算为 2.74。

So once again, this is just the squared error of that line with n points.

所以再一次，这只是那条有 n 个点的直线的平方误差。

This is the squared error of the line axis.

这是线轴的平方误差。

And so what we calculated next was the total error, the squared error, from the means of our y values.

所以我们接下来计算的是总误差，平方误差，来自我们的 y 值的平均值。

You put it into this expression for the squared error of the line.

您将它放入此表达式中以获得直线的平方误差。