This document discusses precision and recall, which are metrics used to evaluate the performance of classification models. Precision measures the proportion of predicted positive instances that are actually positive, while recall measures the proportion of actual positive instances that are correctly predicted to be positive. The document also presents formulas for calculating precision, recall, and the harmonic mean of precision and recall.
This document discusses precision and recall, which are metrics used to evaluate the performance of classification models. Precision measures the proportion of predicted positive instances that are actually positive, while recall measures the proportion of actual positive instances that are correctly predicted to be positive. The document also presents formulas for calculating precision, recall, and the harmonic mean of precision and recall.
38. Gale-Shapley Algorithm
• Gale氏とShapley氏が提案したのでその名前から
• Gale, David, and Lloyd S. Shapley. "College
admissions and the stability of marriage." The
American Mathematical Monthly 69.1 (1962): 9-15.
• 日本でも研修医配属の時に使われているらしい
(公益財団法人医療研修推進財団のHPより)