4 ms·
Measuring the predictability of life outcomes with a scientific mass collaboration. http://www.pnas.org/lookup/doi/10.1073/pnas.1915006117 http://www.pnas.org/
by groceryheist 6y ago
Measuring the predictability of life outcomes with a scientific mass collaboration.
http://www.pnas.org/lookup/doi/10.1073/pnas.1915006117 http://www.pnas.org/lookup/doi/10.1073/pnas.1915006117
You might think that it's possible to use machine learning to predict whether people will be successful using established socio-demographic, psychological, and educational metrics. It turns out that it's very hard and simple regression models outperform the fanciest machine learning ideas for this problem.
The way this study was done is also interesting and paves the way for new kinds of collaborative scientific projects that take on big questions. It draws on communities like Kaggle, but applies it to scientific questions not just pure prediction problems.
- thanksforthe42 6y agoLuck/Fortune is so critical. Genetics and net worth can be blown away by a good or bad group of friends. And unfortunately you start having friends before you are concious enough to realize the impact.
- nhf 6y ago> simple regression models outperform the fanciest machine learning ideas for this problem This reminds me of a classic paper: "Improper linear models are those in which the weights of the predictor variables are obtained by some nonoptimal method; for example, they may be obtained on the basis of intuition, derived from simulating a clinical judge's predictions, or set to be equal. This article presents evidence that even such improper linear models are superior to clinical intuition when predicting a numerical criterion from numerical predictors." Dawes, R. M. (1979). The robust beauty of improper linear models in decision making. American psychologist, 34(7), 571. https://core.ac.uk/download/pdf/190386677.pdf https://core.ac.uk/download/pdf/190386677.pdf