1)multi-instance learning多示例学习
1.A method based on multi-instance learning to improve the itembank redundancy checking algorithm is proposed.基于多示例学习方法对题库重复性检测算法进行了改进,其基本思想是:将包含多个子问题的试题重复性检测转化为多示例学习问题。
2.Chinese web index page recommendation, is presented and then addressed through transforming it to a multi-instance learning problem.多示例学习为中文 Web 挖掘提供了一种新的思路。
3.Basing on the techniques of immune evolution and multi-instance learning and focusing on changing environments, large scope environments and unknown environments, this dissertation revolves the localization and path planning problems, which a.本文针对大范围环境、变化环境和未知环境,以免疫进化和多示例学习作为支撑技术,围绕移动机器人在它的运动过程中始终需要解决的定位与规划二个关键问题进行了比较深入的研究,其研究内容涉及基于多图像的定位、并发定位与建图、路径规划、进化与免疫计算和多示例学习等。
英文短句/例句
1.Image Retrieval Algorithm Based on Multiple-instance learning基于多示例学习的图像检索算法研究
2.The Study of Chinese Text Representation and Classification Based on Multi-Instance Learning基于多示例学习的中文文本表示及分类研究
3.Research and Application on Multi-Instance Learning Using Support Vector Machine基于支持向量机的多示例学习研究与应用
4.The Discovery of Region-of-interest based on Multiple Instance Learning Algorithm基于多示例学习算法的用户感兴趣区域发现
5.Research on Evolutionary Navigation of Mobile Robot Based on Immunity and Multi-instance Learning;基于免疫机制和多示例学习的移动机器人进化导航研究
6.Multiple Instance Learning Based Adaboost Algorithm and Its Application in Face Detection;基于多示例学习的Adaboost算法及其在人脸检测中的应用
7.Algorithmic Research for Automatic Image Annotation Based on Color Constancy and Multiple Instance Learning基于颜色恒常和多示例学习的自动图像标注算法研究
8.K-means Clustering Learning Algorithm Based on Multi-instance基于多示例的K-means聚类学习算法
9.Bag-level multi-instance active learning for image retrieval基于包层多示例主动学习的图像检索
10.RESEARCHES ON THE ACQUISITION OF COGNITIVE SKILLS BASED ON LEARNING FROMEXAMPLES;基于示例学习的认知技能获得的研究
11.An Experimental Study on Mathematics Learning from Example and by Doing;小学生数学示例学习的信息加工过程实验研究
12.The Effects of External Cues on the Self-Regulated Learning Process of Students in Multimedia Learning外在暗示线索对学习者在多媒体学习中自我调节学习过程的影响
13.He doesn't manifest much interest in his studies.他对学习没表示出多大兴趣。
14.The Case of the Inquiry Learning in the Demonstration Experiment of Mini-Transmutation--The Thinking on Teaching Model of Inquiry Learning;“微小形变演示实验”的研究性学习案例——对研究性学习教学的思考
15.The Research of Learning from Examples Based on Interval Numbers and Interval-Valued Programming;基于区间值的示例学习与区间规划的研究
16.Design of an Exploratory Learning Course Based on Web and Its Inspiration;基于网络的探究性学习课例设计及其启示
17.Design and Application of a Fuzzy Classified Rule Based on Learning from Fuzzy Examples;基于模糊示例学习的蠓虫分类规则的设计
18.Programming example of multimedia study-scheme of the Basic Application of Computer;《计算机应用基础》多媒体学案设计示例
相关短句/例句
multiple-instance learning多示例学习
1.A method for image retrieval based On salient points feature multiple-instance learning;基于显著点特征多示例学习的图像检索方法
2.In the multiple-instance learning, many feature are irrelevant to find the target function, and the Citation-KNN algorithm is highly sensitive to the curse of dimensionality, so the FS -Citation -KNN algorithm was proposed based on the feature selection.在多示例学习中,有许多属性相对于我们发现目标函数来说是无关的,而且就Citation-KNN算法而言,该算法对维度灾难的问题是十分敏感的,由此本文提出了一种基于特征选择的FS-Citation-KNN算法,该算法不仅考虑了特征选择的问题,还考虑到对于待测包其近邻的距离对于分类的影响。
3)multiple instance active learning多示例主动学习
1.By extensively studying the characteristics of active learning in multiple-instance setting,the multiple instance active learning problem(MIAL) was categorized into three paradigms,i.通过详细分析多示例主动学习的特点,提出将多示例主动学习概括为包层、示例层以及混合层次主动学习三种模式;针对包层主动学习,将示例数目统计特征作为重要度量并与样本不确定性相结合,提出一种新的样本选择策略。
4)learning from examples示例学习
1.Study on learning from examples based on rough sets theory.;基于粗糙集理论的示例学习研究
2.Integer- programming model for learning from examples and feature subset selection based on extension matrix;示例学习与特征选择的规划模型方法
3.To discern positive and negative example fully, feature subset selection plays a great role in learning from examples.特征选择是示例学习的关键 ,直接关系到获取的概念的优劣。
5)multi-instance multi-label learning多示例多标记学习
6)multiple-instance learning多例学习
1.Region-Based Image Annotation Using Heuristic Support Vector Machine in Multiple-Instance Learning使用基于多例学习的启发式SVM算法的图像自动标注
延伸阅读
部分学习与整体学习部分学习与整体学习part learning and whole learning 部分学习与整体学习(part learningand whole learning)在运动学习和记忆学习中，根据对学习内容的处理方式可以分成部分学习和整体学习。部分学习就是将材料分成几个部分，每次学习一个部分:整体学习就是每次学习整个材料。一般来讲，整体学习的效果优于部分学习。但是，课题复杂彼此没有意义联系的材料，用部分学习的效果好:课题简短或具有意义联系的材料，用整体学习的效果好。在进行学习时，可以将部分学习与整体学习结合起来，先进行整体学习再进行部分学习，或者相反。这种相互结合的学习方式叫做综合学习，效果更好些。 (周国帕撰成立夫审)
