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数据挖掘导论中的K近邻聚类算法，用C++编写而成。-Introduction to Data Mining of the K neighbors clustering algorithm, using C++ has been prepared by.
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数据挖掘算法源码，有聚类算法、分类算法、神经网络分类算法-Source of data mining algorithms, a clustering algorithm, sorting algorithm, neural network classification algorithm
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Many of the pattern fi nding algorithms such as decision tree, classifi cation rules and clustering
techniques that are frequently used in data mining have been developed in machine learning
research community. Frequent pattern and asso
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weka全名是怀卡托智能分析环境（Waikato Environment for Knowledge Analysis），是一个公开的数据挖掘工作平台，集合了大量能承担数据挖掘任务的机器学习算法，包括对数据进行预处理，分类，回归、聚类、关联规则以及在新的交互式界面上的可视化-full name is weka intelligent analysis environment Waikato (Waikato Environment for Knowledge Analysis), is an o
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数据挖掘相关算法集合，有聚类、神经网络、遗传算法等的代码实现-Data mining correlation algorithm collection has clustering, neural networks, genetic algorithms, such as the code implementation
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clustering algorithm in .NET ofr data mining
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数据挖掘 统计学习 分类聚类离散点分布插件小程序-Statistical learning data mining classification clustering distribution of discrete points applet plug-ins
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经典的数据挖掘算法的源代码，包括分类、聚类、关联规则等，非常有用。-Classical data mining algorithms of source code, including classification, clustering, association rules and so on, very useful.
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Entropy Based Subspace Clustering for Mining Data - ENCLUS - a new version of PROCLUS algorithm for clustering high dimensional data set.-Entropy Based Subspace Clustering for Mining Data- ENCLUS- a new version of PROCLUS algorithm for clustering hi
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Weka是一个超强功能的machine learning开发包-Weka is a collection of machine learning algorithms for data mining tasks. The algorithms can either be applied directly to a dataset or called from your own Java code. Weka contains tools for data pre-processing, clas
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This package contains a MATLAB implementation of the cluster
visualization tool CLUSION as described in
A. Strehl and J. Ghosh, "Relationship-based Clustering and
Visualization for High-dimensional Data Mining", Special
Issue on Mining Web
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A distributed PSOSVM hybrid system with feature selection and parameter optimization
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This study proposed a novel PSO–SVM model that hybridized the particle swarm optimization (PSO) and support vector machines (SVM) to
improve the clas
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K-means Clustering in data mining
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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
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一个实现数据挖掘算法的系统。包括预处理，决策树，聚类，关联规则等算法。-A system for data mining algorithms. Including pretreatment, decision trees, clustering, association rules algorithm.
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整体介绍数据挖掘定义及过程，对预处理、聚类、分类、关联规则讲解-Definitions and overall presentation of data mining process, pretreatment, clustering, classification, association rules explained
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在2006年9月召开的ICDM会议上，邀请了ACM KDD创新大奖(InnovationAward)和
Top 10 Algorithms in Data Mining
IEEEICDM研究贡献奖(Research Contributions Award)的获奖者们来参与数据挖掘10大算
法的选举，每人提名10种他认为最重要的算法-Classification，Statistical Learning，Top 10 Algorithms in Data Mining，material
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蚁群聚类算法是基于蚁穴清理行为的聚类算法。
在诸多聚类算法中，蚁群算法是一种较新且较高效率的算法。蚁群算法在数据挖掘聚类中的应用所采用的生物原型为蚁群的蚁穴清理行为和蚁群觅食行为。-Ant clustering algorithm clustering algorithm is based on the nest cleaning action.
In many clustering algorithm, ant colony algorithm is a relatively new
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Data mining clustering massive data into specified group
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数据挖掘介绍，包括数据预处理，可视化，预测建模，关联分析，聚类和异常检测(Data mining introduces data preprocessing, visualization, predictive modeling, association analysis, clustering, and anomaly detection)
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