2) inductive learning
归纳学习
1.
The Research of IDSS Based on Inductive Learning and Case-Based Reasoning;
基于归纳学习和范例推理的智能决策支持系统的研究
2.
Artificial intelligence-based inductive learning method was analyzed.
分析了基于人工智能中的归纳学习方法,提出了一种针对挤压锻造工艺优化的基于数值仿真归纳知识的混合优化方法,并通过一个挤压锻造的实例验证了该方法的有效性。
3) Induction learning
归纳学习
1.
Furthermore, a hybrid learning model combining learning from cases and case\|based reasoning is put forward by virtue of intelligent agents, and the basic framework of the model is also given in which induction learning agents coordinate by a reinf.
构成此框架的各归纳学习agent在专家的协助下,可通过加强学习机制相互促进。
2.
Unlike other improvement works, this paper proposes a method that conducts evolution to keep the balance through induction learning.
不同于现有的其它改进 ,论文采用归纳学习的方法来引导进化过程趋于这一平衡 ;文中采用归纳学习的方法 ,从进化历史进程中抽取出能反映过去进化的错误和成功的规则 ,进而用它们来引导后续的进化过程 ,保证在避免重复错误的同时加速进化 。
3.
This paper proposes a new algorithm called LAID(learning algorithm as inverse deduction) considering the difficulty of traditional induction learning.
针对传统归纳学习的困难,提出一种新的逆演绎的学习算法。
4) fuzzy learning
模糊学习
1.
In this paper, a web page classification with feature selection and fuzzy learning is proposed.
本文提出了一种基于相似度的特征选择算法和适应模糊学习算法来实现分类 。
2.
The design and implementation of a phosphorus removal fuzzy controller with fuzzy learning mechanism are discussed.
文章系统地介绍了具有模糊学习机制的污水脱磷模糊控制器的设计与实现，提出了模糊学习的概念、原理和方法，给出了基于模糊控制表（查询表）的学习算法。
3.
Fuzzy learning vector quantization(FLVQ) algorithm outperforms the hard competitive vector quantization in that it reduces the dependence of the resulting codebook on the initial codebook selection, yet it has the disadvantages of slow convergence and easy to be trapped in local minima.
模糊学习矢量量化算法 (FL VQ)虽然解决了硬的竞争学习对初始码本的依赖性问题 ,但收敛速度变慢 ,且仍无法克服陷入局部最小 。
5) fuzzy decision tree induction
模糊决策树归纳
1.
Clustering-Based Data Preprocessing s Impact on Fuzzy Decision Tree Induction;
基于聚类的数据预处理对模糊决策树归纳的影响
2.
During the fuzzy decision tree induction,the triangular membership function is often used for the fuzzification of data preprocessing.
在模糊决策树归纳过程中,数据的模糊化预处理通常使用三角形隶属函数,该隶属函数的中心点参数将决定数据模糊化的效果,进而影响模糊决策树的执行效率、精度和规模。
6) FRI
模糊法则归纳法
1.
Fuzzy Rule Induction(FRI) is an advanced new tool in data mining.
模糊法则归纳法(Fuzzy Rule Induction using GMDH,简称FRI方法)是近年来兴起的非参数数据挖掘技术,它将模糊建模技术和自组织数据挖掘建模技术相结合,在金融、经济等领域已经得到了成功运用。
补充资料：归纳性概念学习法
归纳性概念学习法
inductive concept learning approach
归纳性概念学习法(induetive eoneeptlearning approaeh)通过比较、对比刺激学习概念的方法。在这种学习中，教师先提供一些所要学习的概念的具体实例，然后通过归纳得出定义。让学生自己比较和对比刺激，能培养学生形成和发现概念的能力。所用时间常较演绎性概念学习法长。 (蒋兆灿撰车文博审)
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条