| 1. | We should adopt different parameter to get the optimal learning machine
训练中需要采用不同的参数，以求得最佳学习机。 |
| 2. | Go on listening , reading , recording and study the materials in learning machines
此环节是使学生进一步养成利用学习机自主学习的习惯，使学生的英语水平得到提高。 |
| 3. | The support vector machine ( svm ) is a novel type of learning machine which has some remarkable characteristics such as good generalization performance , the absence of local minima and fast computing speed
摘要支持向量机( svm )是一种新颖的机器学习方法，具有泛化能力强、全局最优和计算速度快等突出优点。 |
| 4. | ( 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。 |
| 5. | Aiming at the relativity between repeated or similar samples and characteristic parameters during diagnosis of characteristic data , an effective data analysis approach for characteristic data compression from bi - direction is presented , which can reduce the burden of learning machine without losing the connotative characteristic knowledge of characteristic data
摘要对诊断特徵数据中重复或相似事例样本和特徵参量之间可能针存在的相关性，提出一种有效的特徵数据双向压缩预处理方法，该法在不损失数据隐含的特徵知识的前提下，能有效降低学习机器的学习负担。 |
| 6. | Basing on it we bring forward the disambiguation strategy using rule techniques and statistics techniques . in rule model , the acqusition method of rules base is improved . we use the part - of - speech of syntactic category to replace the syntactic category . in addition , statistics method is used to help to construct the rule base . in statistics model , the concept of learning machine - made is presented . in according to the result of learning , the method of calculating transition probabilities and symbol probabilities are amended
在规则方法中，改进了规则库的构建方法，用兼类词词性代替兼类词本身，并尝试使用统计辅助构建规则库；在统计方法中，在二元语法模型基础上引入了学习机制的概念，根据学习结果对词性概率和词汇概率的获取方法进行了修正。 |
| 7. | Since the early nineties last century , machine learning techniques such as artificial neural networks ( ann ) have been attempted in flood forecast areas , such as rainfall - runoff modeling and stream flow forecasting , with some valuable experiences achieved . this paper presents several precise , reliable and practical flood forecast models based on some new style learning machines . their performances were valued in case studies
本文结合机器学习技术，从寻找易用的、准确的、可靠的、实用性强的洪水预报方法的角度出发，建立了多种基于新型的学习机器的洪水预报模型，并通过这些模型在实例中的表现，对它们的性能进行了评价，提出了几种基于学习机器的洪水预报解决方案。 |
| 8. | And the support vector machine ( svm ) is a new kind of learning machine , which is based on the statistical learning theory . its complete theory and excellent performance make a potential future for mine intelligence . the aim of this thesis is to realize 3 - class underwater targets " recognition by means of data mining technique
其中的支持向量机技术是在统计学习理论框架下提出的一种新的学习机器，其完备的理论基础和优良的推广性能，为水雷兵器引信技术的智能化指引了一个很有发展潜力的方向。 |
| 9. | This article criticizes the theoretic basis of mechanism in perspective of student in comenius " " on the clock " , criticize the idea regarding students as learning machines , interrogates locke ' s idea that " the mind is like a piece of white paper , there no marks and ideas on it " deconstruct the absolute hegemony education to the students " development and teachers to students , criticizes kant ' s absolute ration and human nature ' s permanence , generalization , criticizes kant ' s idea that human is existing of rational animal , criticizes kant ' s educational claim that children absolute subject to ration , and criticizes herbart ' s theory that teachers is the center which is influenced by kant
在文章中，批判了夸美纽斯“时钟论”学生观的理论基础? ?机械论，批判了把学生看作“学习的机器”的观点；对洛克的儿童心灵犹如“一张白纸，上面没有任何记号，没有任何观念”的观点进行了质疑，解构了教育对学生成长、教师对学生教育的绝对霸权；批判了康德的绝对理性以及人性的永恒性、普遍性，批判了康德的“人是理性动物的存在”的观点，批判了康德“儿童绝对服从理性”的教育主张，并进一步批判了受康德影响的赫尔巴特的“教师中心论” 。 |
| 10. | Support vector machine is a kind of new general learning machine based on statistical learning theory . in order to solve a complicated classification task , it mapped the vectors from input space to feature space in which a linear separating hyperplane is structured . the margin is the distance between the hyperplane and a hyperplane through the closest points
支持向量机是在统计学习理论基础上发展起来的一种通用学习机器，其关键的思想是利用核函数把一个复杂的分类任务通过核函数映射使之转化成一个在高维特征空间中构造线性分类超平面的问题。 |
