Generalized Linear Regression

Learn to implement closed form solutions, vectorization, and visualization for generalized linear regression.

Single target

Consider a regression dataset D={(x1,y1),(x2,y2),,(xn,yn)}D=\{(\bold x_1,y_1),(\bold x_2,y_2),\dots,(\bold x_n,y_n)\}, where xiRd\bold x_i \in \R^d and yiRy_i \in \R. A function fw(x)=wTϕ(x)f_\bold w(\bold x) = \bold w^T\phi(\bold x) is a generalized linear model for regression for any given mapping ϕ\phi of the input features x\bold x.

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