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Just to be clear (since @RUser4512 hasn't updated his answer), in linear regression you have to solve $$ (X'X)^{-1}X'Y, $$ where $X$ is a $n\times p$ matrix. Now, in general the complexity of the matrix product $AB$ is O(abc) whenever $A$ is $a\times b$ and $B$ is $b\times c$. Therefore we can evaluate the following complexities: a) the matrix product $X'X$ ...


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Let's explore the use case for binary classification. In binary classification the labels are drawn from Bernoulli distribution. For each example the likelihood of the Bernoulli distribution is $p^y*(1-p)^{(1-y)}$. We want to maximize the likelihood of the entire dataset, which means we want to maximize the product of all the examples. Because we want it to ...


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