# Generalized Additive Models em Séries Temporais

2017 May 09Aqui no AlgoBeans provavelmente você verá a melhor explicação sobre modelos aditivos generalizados (Generalized Additive Models) da internet. De forma simples e didática, o post explica tudo sobre essa técnica.

*Therefore, google search trends for persimmons could well be modeled by adding a seasonal trend to an increasing growth trend, in what’s called a generalized additive model (GAM).*

*The principle behind GAMs is similar to that of regression, except that instead of summing effects of individual predictors, GAMs are a sum of smooth functions. Functions allow us to model more complex patterns, and they can be averaged to obtain smoothed curves that are more generalizable.*

*Because GAMs are based on functions rather than variables, they are not restricted by the linearity assumption in regression that requires predictor and outcome variables to move in a straight line. Furthermore, unlike in neural networks, we can isolate and study effects of individual functions in a GAM on resulting predictions.*