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Artificialintelligence
- 详细介绍了贝叶斯理论,神经网络,模糊集合,粗糙集,遗传算法的原理与应用等。 -Details of the Bayesian theory, neural networks, fuzzy sets, rough sets, genetic algorithm theory and applications.
fs_entropy
- data reduction with fuzzy rough sets or fuzzy mutual information
fs_neighbor
- fuzzy rough sets or fuzzy mutual information
Matlabcode
- 粗糙集代码 data reduction with fuzzy rough sets or fuzzy mutual information fuzzy preference rough set based feature evaluation and selection -Rough code data reduction with fuzzy rough sets or fuzzy mutual information fuzzy preference rough set bas
datareduct
- 基于香浓熵的属性简约,用于属性约简,以便分类-data reduction with fuzzy rough sets or fuzzy mutual information
GIS
- 本文首先介绍了粗糙集理论的基本概念,包括等价关系、不可分辨关系、上下近似、粗糙集和简约;并且从空间数据挖掘、遥感影像处理、GIS 不确定性、GIS 数据分析、模糊地理对象建模和粗糙集与其它软计算方法的结合等六方面概述了粗糙集理论在GIS 数据处理中应用的进展-This paper introduces the basic concepts of rough set theory, including the equivalence relation, can not distinguish be
dxckj
- 本文首先介绍了粗糙集理论的基本概念,包括等价关系、不可分辨关系、上下近似、粗糙集和简约;并且从空间数据挖掘、遥感影像处理、GIS 不确定性、GIS 数据分析、模糊地理对象建模和粗糙集与其它软计算方法的结合等六方面概述了粗糙集理论在GIS 数据处理中应用的进展-This paper introduces the basic concepts of rough set theory, including the equivalence relation, can not distinguish be
lgorit
- 粗糙集与模糊集的连续值域决策表的离散化算法-Based on rough sets and fuzzy sets continuous range of discrete decision table algorithm
22222222
- data reduction with fuzzy rough sets or fuzzy mutual information
7.-A-comparative-study-of-fuzzy-sets-and-rough-se
- this paper reviews and compares theories of fuzzy sets and rough sét. Two approaches for the formulation of fuzzy sets are reviewed, one is base on many-valued logic and the other is based on model logic-this paper reviews and compares theories of fu
matlab-data-mining
- 数据挖掘(Data Mining)阶段首先要确定挖掘的任务或目的。数据挖掘的目的就是得出隐藏在数据中的有价值的信息。数据挖掘是一门涉及面很广的交叉学科,包括器学习、数理统计、神经网络、数据库、模式识别、粗糙集、模糊数学等相关技术。它也常被称为“知识发现”。知识发现(KDD)被认为是从数据中发现有用知识的整个过程。数据挖掘被认为是KDD过程中的一个特定步骤,它用专门算法从数据中抽取模式(patter,如数据分类、聚类、关联规则发现或序列模式发现等。数据挖掘主要步骤是:数据准备、数据挖掘、结果的解释
classificiation-algorithm-overview
- 机器学习领域经典分类算法综述,包括Decision Tree(ID3、C4.5(C5.0)、CART、PUBLIC、SLIQ和SPRINT算法),三种典型贝叶斯分类器(朴素贝叶斯算法、TAN算法、贝叶斯网络分类器),k-近邻 、 基于数据库技术的分类算法( MIND算法、GAC-RDB算法),基于关联规则(CBA:Classification Based on Association Rule)的分类(Apriori算法),支持向量机分类,基于软计算的分类方法(粗糙集(rough set)、遗传
Program
- 模糊逻辑变精度粗糙集算法程序,数据挖掘故障诊断规则,27条训练集,8属性,5类故障。-Rough set of variable precision fuzzy logic algorithm procedures, data mining fault diagnosis rules, 27 train sets, eight properties, five fault.