Description: 我一直覺得 SVM 是個很有趣的東西，不過也一直沒辦法 (mostly 衝堂) 去聽林智仁老師 的 Data mining 跟 SVM 的課； 後來看了一些網路上的文件跟聽 kcwu 講了一下 libsvm 的用法後，就想整理一下，算是對於並不需要知道完整 SVM 理論的人提供使用 libsvm 的入門.-SVM I always think that is something very interesting, but we also have no way (mostly Chong Tong) to listen to the teachers Linzhiren Data mining with SVM's class; Later read some documents on the Internet kcwu listen to speakers with a little libsvm usage, wanted to tidy up, is not for the need to know SVM complete theory for the use of libsvm entry. Platform: |
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Author:军 |
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Description: ID3+C4.5的源程序。用于数据挖掘决策算法的一个实例。-ID3 C4.5 of the source. Data Mining for a decision algorithm examples. Platform: |
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Author:张飞 |
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Description: BP学习算法应用——模式分类
应用动量BP学习算法对UCI提供的经典数据库——鸢尾属植物数据库进行分类，速度快，精度高。iris.arff为数据库文件，可用Weka数据挖掘软件打开。Iris.csv为源代码读取的数据文件，通过Weka软件转换得到。
将源文件Iris_classify.m和Iris.csv文件放入matlab的work文件夹中直接运行即可。-BP learning algorithm applications- the application of pattern classification momentum BP learning algorithm to provide a classic UCI database- iris database classification, high speed and accuracy. iris.arff for the database file that can be used to open Weka data mining software. Iris.csv for the source code to read the data files have been converted through Weka software. Iris_classify.m the source document and document Iris.csv Add matlab folder of work can be directly run. Platform: |
Size: 5120 |
Author:Michael_M |
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Description: 使用matlab软件进行程序设计中的五个数据挖掘源程序代码。-Using matlab software programming for the five data mining source code. Platform: |
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Author:左秀霞 |
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Description: 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、结果的解释评估。-Data Mining (Data Mining) stage must first determine the mission or purpose of the excavation. The purpose of data mining is to draw valuable information hidden in the data. Data mining is an interdisciplinary involving a wide range, including control study, mathematical statistics, neural networks, databases, pattern recognition, rough sets, fuzzy mathematics and other related technologies. It is also often referred to as the " knowledge discovery" . Knowledge discovery (KDD) is that the whole process is to discover useful knowledge from data. Data mining is a particular step in the KDD process, with a special algorithm (patter, such as data classification, clustering, association rules discovery or sequential pattern discovery. Extracted from the data model and data mining major steps: data preparation, data mining, interpretation of the results evaluated. Platform: |
Size: 12288 |
Author:dlufl |
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Description: natlab数据挖掘与分析实战，可以让读者获得真实的数据挖掘学习与实践环境，更快、更好的学习数据挖掘知识与积累职业经验。-MATLAB data mining and analysis,focus on the combination of data mining theory and project case practice. Platform: |
Size: 15266816 |
Author:木 |
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