According to Wiki, feature scaling is a method used to standardize the range of independent variables or features data. In data processing, it is also known as data normalization and is generally performed during the data preprocessing step. Advertisements
I know, for many of us, when we first encounter these two terms it is a bit hard to understand the difference, especially because sometimes both unobserved errors, but also residuals are simply called “errors”.
A cost function is a function that maps an event or values of one or more variables onto a real number intuitively representing some “cost” associated with the invent. An optimization problem seeks to minimize a loss function. An objective…
This is the excerpt for your very first post.