主动学习

  • 网络Active learning;active learner;Proactive Learning
主动学习主动学习
  1. 一种新的SVM主动学习算法及其在障碍物检测中的应用

    An SVM Active Learning Algorithm and Its Application in Obstacle Detection

  2. 多分类SVM主动学习及其在遥感图像分类中的应用

    Remote sensing lmage classification using active learning with multiclass support vector machine

  3. 基于Web的学习支持系统也一种教学系统,强调以学习者的学习为中心,着意于为学习者营造一个激发主动学习的学习环境。

    Web based learning supporting system is also an instruction system , which focus on the learner and aim at creating more active learning environment .

  4. 基于主动学习SVM的蒙文文本分类系统的设计与实现

    The Design and Implement of a Mongolian Text Classifier Based on Active Learning SVM

  5. 在前两步的基础上,针对上面提出的问题,设计了一种基于SVM的多模态主动学习算法,并进行了实验验证。

    Based on the former two steps , we propose a multi-modality active-learning method , and validate the proposed method .

  6. 主动学习是一个当今比较热门的研究领域,将SVM与主动学习结合起来能够解决更多的实际问题。

    At present , the active learning has become a hot research issue . Combining the SVM with active learning will solve more practical problems .

  7. 本文以SVM为基准学习器,采用主动学习方法,针对不同维度的数据提出了相应的SVM主动学习算法。

    This thesis proposes two SVM active learning approaches for different dimensional data , employing SVM as a basic learner , and adopting active learning .

  8. 同时使用评委会主动学习的方法,在分类过程中,选择争议最大的bug请求其类别,进行自主学习,然后再对bug进行分配。

    Meanwhile , the method of query by committee is used , which selects the most controversial bugs to ask for their category labels for active learning .

  9. 研究了一种用SVM进行主动学习的方法,该方法与普通的SVM方法相比,在保证分类性能的前提下,可有效的提高效率。

    An active learning method using SVM is researched . Comparing with the general SVM , it can improve the capability on the premise of keeping correctness of the classifier .

  10. 实验表明,基于主动学习的SVM算法是有效的,能够在保证分类器性能的前提下有效地减少了学习样本的数量。

    Finally , experiment shows that the SVM based on active learning is effective , which can effectively reduce the number of samples on the premise of keeping correctness of the classifier .

  11. 基于主动学习的SVDD预警技术

    Support vector data description early warning technique based on active learning

  12. 结果:脑康泰胶囊可显著增强AD大鼠被动学习和主动学习的能力,调节脑组织中单胺类递质含量及血液中相关激素水平,并显著改善AD模型大鼠的脑电图。

    RESULTS : Naokangtai capsule could increase the ability of memory and learning of AD rats , adjust the level of monoamine transmitters in the brain and hormones in the blood and improved electro encephalogram of AD rats significantly .

  13. 针对高维数据提出基于向量余弦的SVM主动学习策略,称为CosSVMactive。

    Then the unlabeled most valuable samples will be labeled by experts . ( 2 ) For high-dimensional data , an SVM active learning strategy based on vector cosine is presented , named Cos_SVMactive .

  14. 基于分类损失的主动学习借鉴到EM学习中,可以自主选择有用的未标注样本来请求用户标注,当把这些样本加入训练集后能够最大程度减少模型对未标注样本分类的不确定性。

    The classification loss method of active learning combined with EM results in maximal reduction of the uncertainty of classifying unlabeled examples through actively selecting useful unlabeled examples to label and adding them to training data .

  15. 通过实验测试,证明这两种主动学习算法在达到目标正确率时所需的标注代价小于传统的随机采样、Uncertainty采样和QBC采样算法。

    The experiment shows that these two proposed algorithm can achieve the target accuracy with fewer labeling cost than traditional random sampling , Uncertainty sampling and QBC sampling algorithms . 6 .

  16. Y迷宫测试20、40、60d龄仔鼠主动学习和记忆能力。

    For active learning and memory ability , the 20-day old , 40-day old and 60-day old offspring were tested by Y maze .

  17. 讨论了利用QBC(委员会投票选择)的主动学习方法来学习贝叶斯网络分类器,通过对基于投票熵和基于KL-divergence的QBC算法的研究,指出了两者存在的缺陷;

    This paper discussed the Query-by-Committee ( QBC ) methods of active learning . The disadvantages of QBC based on vote entropy and KL-divergence were presented .

  18. 结合委员会成员投票熵和相对熵,改进了基于委员会选择算法(QBC)的主动学习,并应用基于该算法的主动贝叶斯网络对电信客户信用风险分类进行建模。

    This paper modifies the query-by-committee ( QBC ) method of active learning by combining vote entropy and kullback-leibler divergence for learning TAN classifier to model telecom clients ' credit classification .

  19. 我们提出了联合CEM和SVM进行主动学习的一种算法,该算法将主动学习过程分为两个步骤:第一步利用CEM算法发掘和查询置信区域;

    One pool-based Active Learning algorithm with Competitive Expectation-Maximization ( CEM ) algorithm and Support Vector Machine ( SVM ) is proposed by us , which consists of two stages : in the first stage , applying CEM algorithm to discover the confident regions of unlabeled data in the pool ;

  20. 如何充分发挥学生的主动学习精神;

    How fully develop the initiative spirits of students in study ;

  21. 试探使学生主动学习的教学策略

    An Inquiry into the Teaching Strategies of Making Students Study Autonomously

  22. 透过对一个主要设计制造专案的主动学习来达到课程目的。

    Subject relies on active learning via a major design-and-build project .

  23. 主动学习者可能向他们的教授或同学寻求帮助。

    Active learners may seek assistance from their professors or peers .

  24. 4为学生主动学习提供平台(如活动)。

    Provide a platform for activities for students ' autonomic learning .

  25. 自主学习是一种主动学习、独立学习、自控学习。

    Autonomous learning is active learning and independent learning , automatic learning .

  26. 课堂上学生积极主动学习的意愿随着年龄的增长而递减。

    Students ' active learning in classroom decreases with age and growth .

  27. 探索主动学习体育的教学策略

    Searching after the PE Teaching Strategy of the Initiative Studying

  28. 在小学数学教学中引导学生主动学习

    Guiding the Students to Learning Actively in the Maths Teaching

  29. 中学化学教学培养学生主动学习的途径

    How to train students ' ability to learn chemistry actively

  30. 激发学生学习兴趣诱导学生主动学习

    Stimulate Students ' Interest and Guide Students to Learn Actively