New answers tagged genetics
Keeping it simple: adding the square of the variable allows you to model more accurately the effect of age, which may have a non-linear relationship with the independent variable. For instance, the effect of age could be positive up until, say, the age of 50, and then negative thereafter. Adding the age squared to age, allows you to model the effect a ...
Most of the kernels (assuming you mean kernel trick as in SVM) used are of an infinite dimension, you will have trouble storing them in our puny not-really-a-turning-machine-no-infinite-memory computers. You will need to use an approximate version of the feature vectors, such as those obtained using Nystrome's method or Random Fourier Features.
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