statistical learning theory

基本解釋

Support Vector Machines (SVM) is a novel powerful learning method developed on Statistical Learning Theory, and of many special advantages.
支持向量機是在統(tǒng)計學習理論基礎上發(fā)展而來的一種新的通用學習方法，具有很多獨特的優(yōu)點。
A support vector machine is a new machine learning technique developed on the basis of statistical learning theory, and it is the most successful realization of statistical learning theory.
支持向量機是在統(tǒng)計學習理論基礎上發(fā)展起來的一種新的機器學習方法，同時也是到目前為止統(tǒng)計學習理論最成功的實現(xiàn)。
The support vector machine is a novel type of learning technique, based on statistical learning theory, which uses Mercer kernels for efficiently performing computations in high dimensional spaces.
支撐矢量機是根據(jù)統(tǒng)計學習理論提出的一種新的學習方法，即使用核函數(shù)在高維空間里進行有效的計算。