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lmann2
Posts: 156
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Posted 20:25 Feb 11, 2016 |
Just for clarification (because we didn't do a example in class): The hypothesis function multiples each row of our features matrix by the theta vector. After that process we subtract our actual value y_i from the vector that returns from the hypothesis (this is a 1x1 single value). Y is a vector, so y_i should be a single value as y in this case is a 415x1 vector. Correct? We multiply it by the currect x_j value and repeat this process for all x_ j... Also dumb question, but do we also need to scale our actual values y ?
Last edited by lmann2 at
21:43 Feb 11, 2016.
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msargent
Posts: 519
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Posted 09:01 Feb 12, 2016 |
There are different ways to do the gradient, that's one of them: you can use a loop as well. Don't scale the y value. |