| 1. | Shiga - like toxin , slt
志贺样毒素 |
| 2. | Browse the first chapters of this book if you want to go deeper into the foundations of slt
如果你想要更深入的了解统计学习的基本原理，请浏览本书的前几章节。 |
| 3. | Browse the first chapters of this book if you want to go deeper into the foundations of slt
如果你想要更深入的了解统计学习理论的基本原理，请浏览本书的前几章节。 |
| 4. | Support vector machine ( svm ) is used as the implementation basis , which is a tool of statistical learning theory ( slt )
在探索手写字符识别的方法上采用了统计学习理论，利用支撑向量机svm作为基本的识别工具。 |
| 5. | The method to determin reversal electric field was provided , and on the base of experiment data in this method , a new periodicity poled waveform and period was designed
根据该方法的实验数据设计出了一种新的周期性极化波形和周期。实验的结果有:通过实验测出了slt晶体的极化反转电压为1 . 6kv / mm 。 |
| 6. | Slt is a machine learning theory based on samples , which was started by v . vapnik in the 1970s and matured to form a complete theoretical architecture in the middle of 1990s
V . vapnik等人从六、七十年代开始致力于此方面的研究，到九十年的中期，其理论的不断发展和成熟，已基本形成一套比较完整的理论体系。 |
| 7. | Chapter 2 has systematically discussed machine learning problem , which is the basic of svm , with statistical learning theory or slt . secondly , chapter 3 has educed the optimal hyperplane from pattern recognition
第二章探讨了支持向量机理论基础? ?学习问题，尤其是对vapnik等人的统计学习理论（ slt ）结合学习问题作了系统的阐述。 |
| 8. | ( 4 ) support vector machine ( svm ) is a novel powerful learning machine , which can solve small - sample learning problem better . the basic ideas of statistical learning theory ( slt ) and svm are introduced , and the characteristics of svm are illuminated
本文参考前人的工作，对统计学习理论和支持向量机的相关知识进行了介绍，分析了svm模型的特点，并对选用不同的模型和参数对支持向量机模型的影响进行了探讨。 |
| 9. | Statistical learning theory ( slt ) is based on the structural risk minimization ( srm ) principle , and it is a new set of theory system , which specially aims at machine learning issues under the circumstances of small - sample . based on this slt , supporting vector machine ( svm ) method has been developed as a new machine learning algorithm and also practical applications of slt
统计学习理论建立在结构风险最小化原则基础上,它是专门针对少样本情况下机器学习问题而建立的一套新的理论体系,支持向量机就是在统计学习理论这一基础上发展起来的一种新的机器学习算法,它是统计学习理论的具体应用。 |
| 10. | The dissertation mainly aims at applying several active machine learning strategies to intrusion detection and systematically studies signal analysis techniques of intrusion detection based on statistical learning theory ( slt ) , symbol inductive learning theory and genetic learning method . meanwhile , performance comparison and evaluation among intrusion detection techniques based on different machine learning strategies are presented according to computational learning theory and statistical hypothesis test methodology . intrusion detection is regarded as a pattern recognition problem in term of statistical learning theory ; i
本文的主要工作是将目前几种有生命力的机器学习策略应用于入侵检测技术中,论文从入侵检测的不同视角出发,系统深入地研究了统计学习理论、基于符号的归纳学习理论和遗传学习方法在入侵检测信号分析中的应用技术,并在可能近似正确( pac )学习框架下,利用计算学习理论和统计假设检验方法对基于不同机器学习策略的入侵检测方法进行了性能比较和评估。 |
