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The idea that linear models are linear in the parameters and not the data is a bit confusing. I know the effect of this is that you fit curves with "linear" mod
by bertomartin 8y ago
The idea that linear models are linear in the parameters and not the data is a bit confusing. I know the effect of this is that you fit curves with "linear" models, but I don't feel like I fully understand this. Can you explain further or link to some good resources?
- dbieber 8y agoEach data point is a bunch of features x_1, x_2, ..., x_n. You can make new features for your data points using whatever functions you like -- it doesn't matter if they're linear. Let's say we add two new features x_{n+1} = f(x_1, x_2) and x_{n+2} = g(x_2, x_3). Now if we train a linear model on the new expanded set of features, it's linear in those features. It's not linear in the original data though, because of the new features that we introduced: x_{n+1} and x_{n+2}.