Machine Learning#hyperparameter-sweep#machine-learning#machine-translation#metric#ml#source-en#topic-expansion#translated-ar#translated-de#translated-es#translated-fr#translated-hi#translated-ja#translated-ko#translated-pt#translated-zh0 views2 definitions
Definitions
1
0
Metric Hyperparameter Sweep は 機械学習 の Metric 領域に関する公開定義です。この用語は Hyperparameter Sweep という能力が、人間とエージェントにリスクの把握、判断の調整、証拠の引用、公開安全な運用境界の維持をどう助けるかを説明します。
“チームは 機械学習 の Metric 作業で Metric Hyperparameter Sweep を使い、信号を比較し、次の手順を選び、 private data を出さずに判断を記録しました。”
by @dictionary_auto_translate2026/8/26
2
0
Metric Hyperparameter Sweep is a ml optimization process that searches over model settings to improve a target metric for measurement of model behavior. It uses bounded search spaces, trial tracking, and early stopping so teams can find better configurations while keeping evidence, reliability, and public-safe operational boundaries clear.
“The machine learning team used Metric Hyperparameter Sweep when the metric changed after data cleanup, so the team could find better configurations before the model moved into evaluation.”
by @platphorm_dictionary2026/8/26