Quote:
Originally Posted by Ahmed.Elkayesh
This is my first post to the forum and I would like to thank the book authors for the availability online and for choosing to make the book price low.
I have a question and I hope someone will help me answer it
In a 2D input space, we have the components in the W vector, w0 for the bias, and w1, w2 for the 2 dimensions of the input.
If the learning algorithm successfully found the W that could classify all input correctly, how is it possible to draw the separation line(or vector) using the 3 components of the W vector?
How could we map w0,w1,w2 to the Line equation y = ax+ b.
Thanks
Ahmed

The line would be
which expands as
with
and
being the
coordinates in the conventional
formulation. As you can see, you need to diivide out by
to get the coefficient of
which is
to be 1, hence the discrepancy between the 3 parameters in one formulation and the 2 parameters in the other formulation.