support vector machine信息详情
支持向量机
vector───n.矢量；带菌者；航线；vt.用无线电导航
vector arena───矢量竞技场
brushes vector───画笔矢量
apsidal vector───半圆形矢量
support───v.支持；帮助；支撑；维持；证实；胜任；忍受；（尤指在财政方面）资助；（在流行音乐会上）当助演；安慰；（计算机）支持……的运行；n.支持；帮助；支撑物；支撑；扶持；物质援助；安慰；（流行乐或摇滚音乐会的）伴奏；技术支持；证据；（战争中的）支援
costate vector───共态向量
vector fonts───矢量字体
disarmed vector───解除防护矢量
coinitial vector───向量共初始
Chapter 4, The Some Development of Support Vector Machine.───第4章，支持向量机的部分进展。
Support Vector machine is a new method of machine learning.───支持向量机是一种新的机器学习方法。
The results show that this method is feasible and the classification accuracy and speed is better than traditional support vector machine.───试验结果表明这种方法是可行的并且分类精度和速度均较传统的支持向量机分类法有所提高。
Pointed out that the concept of knowledge, general classification algorithms and support vector machine classifier.───指出知识学习的概念与一般的知识分类算法和支持向量机分类器。
However, as a newer theory of machine learning field, support Vector Machine is still being developed and constant improved.───然而，作为机器学习领域中相对较新的理论，支持向量机很多方面还处于不断发展完善之中。
The selection method of kernel in the information entropy support vector machine model is one of our in-depth researches.───信息熵支持向量机模型中核函数的选取问题也是我们的重点研究内容之一。
Initial goal concept learned by standard support vector machine algorithm was updated by an updating model.───利用标准的支持向量机算法训练得到初始的目标概念，通过增量式步骤不断更新初始的目标概念。
and a support vector machine regression (SVR) technique is introduced to establish the model of power equipment insulation status change.───研究了支持向量机回归技术，并将其初步应用于绝缘劣化动力建模。
Explores the training problems of support vector machine with large training pattern set, and a new parallel algorithm based on orthogonal array is presented.
And support vector machine model is used to estimate the unmeasured process parameters that are difficult to model with first principle.
To resolve the unclassifiable region of one-against-one support vector machine for multiclass problems, an improved one-against-one support vector machine based on distance measure is presented.
The basic Support Vector Machine for Classification solves the primal problem by solving the dual problem.
The support vector machine(SVM) and a group of annotation rules were used to support documental level annotation and lexical level annotation.
This paper proposes a new Support Vector Machine(SVM) for anomaly intrusion detection method based on Latent Semantic Indexing(LSI).
The support vector machine has avoided the dimension disaster with the inner product operation.
Then, using support vector machine classifier to conduct quality classification on speed ratio control valve.
Support vector machine is a highly performance classification method.