| Turing believed in fairy tales. Gödel believed in ghosts. This was also at the start of the cold war, where the US suspected that the USSR was funding millions to ESP research. One of the most publicized projects was the Stargate Project: Even though a statistically significant effect has been observed in the laboratory, it remains unclear whether the existence of a paranormal phenomenon, remote viewing, has been demonstrated. I think Turing was closer to the machine learning camp than the statistics camp. On that note I'll quote a competitor in the MLSP 2014 Schizophrenia Detection Challenge: To the people that are going to write papers for this one... What really strikes me is the fact that stats fail really hard in this problem. I have a couple of 2-variable combinations that score around 0.87 on training set with logistic regression and a couple of 3-variable combinations with training AUC 0.9 (ish). All results were "statistically significant" at 0.001 (not even 0.01) . I have tried the same selections with SAS, SPSS, R and scikit (with regularization) . All results are consistent (and similar) with all packages, yet again they scored around 0.5 (random) in public and private leaderboard. This makes me think about all the PhDs' thesis and medical science papers I've seen being carried out on mickey mouse sets , claiming statistical significance gives credibility to their findings ... Is machine learning more reliable than stats? I say, if you can't predict it consistently on a hold out set, then you got nothing whatever the t,F,Chi-sq distributions say. KazAnova - https://www.kaggle.com/users/111640/kazanova |
And unfortunately, Gödel believing in ghosts was the least of his problems.