| 1. | Define learnability . would the following set of languages be learnable ? if yes , describe the learning procedure . if no , explain why not
定义可习得性。下列语言组合是可学习的吗？若为是，请描述学习过程。若为否，请解释。 |
| 2. | Define learnability . would the following set of languages be learnable ? if yes , describe the learning procedure . if no , explain why not
请定义习得能力。下列语言组合是可学习的吗？若为是，请描述学习过程。若为否，请解释。 |
| 3. | Training of operative skills is one of the most important learning procedures in vocational and technical education , which has its own features compared with cognitive learning
摘要操作技能的训练是职业技术教育中一种重要的学习过程，与认知学习相比，具有自身的特点。 |
| 4. | The model consists of two parts : the multi - structuring elements filter formed according to the generalized morphological denotation theorem , and an learning procedure to obtain optimal structural parameters
该模型由形态学统一表示定理构成的多结构基元滤波器和结构参数优化学习两个部分组成。 |
| 5. | ( 3 ) the improvement of the incremental learning algorithm in this paper , the shortcomings of the traditional incremental learning procedure are pointed out , and the n corresponding resolving methods are advanced
( 3 ) svm增量学习算法的改进本文中，作者指出了传统的增量学习方法中存在的缺陷，并根据此缺陷提出了相应的解决方法。 |
| 6. | Beside this , space and time arrangement in classroom also get negative influences from the linear use of time just as it been used in the factory and seemed fail to care about students " learning procedure
此外，教育中的时空安排不还受到社会生活当中时间、空间线性化、商品化的影响，学校的时间安排向工业生产的时间安排靠近，倾向于忽视学生真实学习过程的展开，不利于学生的成长。 |
| 7. | This network can be summarized as follows : ( 1 ) about the networks " architecture , it is not fully connected but it uses selective connection between the units of two hidden layers . the number of these units is determined dynamically . ( 2 ) during the learning procedure , a new input - output clustering ( ioc ) method is adopted to select centers
该网络主要有以下特点： ( 1 )网络结构上，两层隐层选择性连接，隐层节点数在学习过程中动态确定； ( 2 )学习规则上，提出一种同时考虑输入输出样本信息的输入一输出聚类( input - outputclustering ， ioc )方法，且聚类中心的形状参数自适应变化。 |
| 8. | In designing a multi - structuring elements filter , combination rules and structuring elements of the morphological transform are determined automatically , and one kind of neural networks is taken for the filter , in optimzing structural parameters of the filter , three computation methods are designed respectively , by adopting some priori information in application fields to guide optimal structural parameter learning procedure , which are the bp adaptive learning algorithm , the heuristic genetic learning algorithm and the inductive simulated annealing learning algorithm
在多结构基元滤波器设计中，通过学习人-机交互选定的目标样本，自动确定形态变换的组合规则及其结构元素，最终以神经网络形式构成滤波器。在结构参数的优化学习中，利用应用领域的先验知识，分别设计了自适应bp学习、启发式遗传学习和引导式模拟退火学习等三种最优化计算方法。 |
| 9. | Therefore , when the student information is returned , the model can update all the item distribution probabilities with the help of self - study ability of the bayesian networks . finally , accurate testing of the mastery of new knowledge is fulfilled , as a result , the teaching and learning procedure is individuated
这样，当有学生的反馈信息时，模型能够通过贝叶斯网络的自学习能力，更新知识项之间的概率分布，从而完成对学生能力及学习状况的预测推理，实现个性化教学。 |
| 10. | Being different from traditional neural network or nn , nn is based on traditional statistics , which provides conclusion only for the situation where sample size is tending to infinity , while svm is based on statistical learning theory or slt , which is a small - sample statistics and concerns mainly the statistic principles when sample are limited , especially the properties of learning procedure
支持向量机( svm )是九十年代中期发展起来的新的机器学习技术，与传统的神经网络( nn )技术不同， svm是以统计学习理论( slt )为基础， nn是以传统统计学理论为基础。传统统计学的前提条件是要有足够多的样本，而统计学习理论是着重研究小样本条件下的统计规律和学习方法的，它为机器学习问题建立了一个很好的理论框架。 |
