CODEWITHSUNDEEP
regressionpredictionscoringbest-fit-curve
genjong
genjong

Reputation: 137

Best fit to model is a poor predictor

For fun, I was trying to make a predictor for how long it would take for George R. R. Martin's The Winds of Winter to be released. My "best" model is the one that had the lowest combined AIC and BIC score (summed together). I tried polynomials of degree 0 to something like 50. The best one of this sort was this, which had a degree of 3 or 4:

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Where the y-axis is the days since A Game of Thrones was released and the x-axis is the number of books released in the A Song of Ice and Fire series. Despite this having the best combined AIC and BIC score, it is a poor predictor, predicting in a way that doesn't make any temporal sense. However, this had the best combined AIC and BIC score (the lowest one). This pointed out to me that my notion that "the best predictor is the one with the lowest combined AIC and BIC score" is flawed. Where have I gone wrong in my thinking, and what kind of scoring criteria would be more appropriate?

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