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計算機科学や機械学習において、Population-Based Incremental Learning (PBIL) とは、最適化アルゴリズムの一つであり、の一つ。遺伝的アルゴリズムの一種であり、個々の個体ではなく、全個体群の遺伝子型(確率ベクトル)が進化する。アルゴリズムはShumeet Balujaが1994年に提案した。このアルゴリズムは標準的な遺伝的アルゴリズムよりもシンプルであり、多くのケースで、標準的な遺伝的アルゴリズムよりも良い結果を出す。
, In computer science and machine learning, … In computer science and machine learning, population-based incremental learning (PBIL) is an optimization algorithm, and an estimation of distribution algorithm. This is a type of genetic algorithm where the genotype of an entire population (probability vector) is evolved rather than individual members. The algorithm is proposed by Shumeet Baluja in 1994. The algorithm is simpler than a standard genetic algorithm, and in many cases leads to better results than a standard genetic algorithm.results than a standard genetic algorithm.
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計算機科学や機械学習において、Population-Based Incremental Learning (PBIL) とは、最適化アルゴリズムの一つであり、の一つ。遺伝的アルゴリズムの一種であり、個々の個体ではなく、全個体群の遺伝子型(確率ベクトル)が進化する。アルゴリズムはShumeet Balujaが1994年に提案した。このアルゴリズムは標準的な遺伝的アルゴリズムよりもシンプルであり、多くのケースで、標準的な遺伝的アルゴリズムよりも良い結果を出す。
, In computer science and machine learning, … In computer science and machine learning, population-based incremental learning (PBIL) is an optimization algorithm, and an estimation of distribution algorithm. This is a type of genetic algorithm where the genotype of an entire population (probability vector) is evolved rather than individual members. The algorithm is proposed by Shumeet Baluja in 1994. The algorithm is simpler than a standard genetic algorithm, and in many cases leads to better results than a standard genetic algorithm.results than a standard genetic algorithm.
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Population-based incremental learning
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