risk minimization

基本解釋

Support vector machine (SVM) is a new general learning machine, which analyzes the consistency of learning and speed of convergence from structure risk minimization principle.
支持向量機(jī)（SVM）是一種新的通用學(xué)習(xí)機(jī)器，它從結(jié)構(gòu)風(fēng)險(xiǎn)最小化的角度，分析了學(xué)習(xí)過程的一致性、收斂速度等。
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As a direct implementation of the structure risk minimization (SRM) inductive principle, SVM provides good performances such as global optimization and good generalization ability.
作為結(jié)構(gòu)風(fēng)險(xiǎn)最小化準(zhǔn)則的具體實(shí)現(xiàn)，支持向量機(jī)具有全局最優(yōu)性和較好的泛化能力。
As a direct implementation of the structure risk minimization(SRM) inductive principle, SVM provides good performances such as global optimization and good generalization abilities.
作為結(jié)構(gòu)風(fēng)險(xiǎn)最小化準(zhǔn)則的具體實(shí)現(xiàn)，支持向量機(jī)具有全局最優(yōu)性和較好的泛化能力。

Research from Vanguard found that semiannual rebalancing can strike a reasonable balance between risk control and cost minimization.
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最小風(fēng)險(xiǎn)
In order to reduce the damages of wrong e-mail classifying, we provided the improved methods of using the risk minimization Bayesian decision and self-adjustment of categorization system.
為減少郵件的誤判對(duì)用戶造成的損害及垃圾郵件漏判造成的影響,提出了相應(yīng)的改進(jìn)措施:使用最小風(fēng)險(xiǎn)貝葉斯決策減少誤判;通過垃圾郵件反饋,對(duì)分類系統(tǒng)進(jìn)行自適應(yīng)調(diào)整,以改善垃圾郵件的漏判問題。
能源科學(xué)技術(shù)
風(fēng)險(xiǎn)極小化