In statistics and machine learning, random multinomial logit (RMNL) is a technique for (multi-class) statistical classification using repeated multinomial logit analyses via Leo Breiman's random forests.
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“Man always made, and still makes, grotesque blunders in selecting and measuring forces, taken at random from the heap, but he never made a mistake in the value he set on the whole, which he symbolized as unity and worshipped as God. To this day, his attitude towards it has never changed, though science can no longer give to force a name.”
—Henry Brooks Adams (1838–1918)