A general 2-class classifier software& SVM ★ was programmed via a stochastic gradient ascent algorithm. 本文利用随机梯度上升算法构建了一套通用二类分类器-SVM★。
The model admits an efficient calculation of the sample path gradient of the network revenue function. The gradient is then used to construct a stochastic steepest ascent algorithm. 该模型对网络收益函数的样本梯度进行了有效的计算,并将梯度应用于构建随机最陡上升算法。