Can some one with expertise explain how the following vectorized format of multiple linear regression is derived from given independent variable matrix with intercept X and dependent variable matrix Y, with m rows and n columns with n theta parameters? In Andrew Ng class, I am bit lost here on how this and non vectorized cost function are same?
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Hari Prasad
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Ah! I think I got the answer. I forgot that what is happening is a square of a vector in the error part of the function. Hence it is transpose of vector.vector. Still not able to understand how X is defined with transposes of all independent variables in above definition, as I believe it is a matrix of dependent variables including intercept.
Hari Prasad
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you got the error for each data point :( X*Theta - y ) when you transpose and do inner product. It is as same as squaring all the errors and taking a sum.
doob
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