Description: 序列模式的概念最早是由Agrawal和Srikant 提出的
序列模式定义：给定一个由不同序列组成的集合，其中，每个序列由不同的元素按顺序有序排列，每个元素由不同项目组成，同时给定一个用户指定的最小支持度阈值，序列模式挖掘就是找出所有的频繁子序列，即该子序列在序列集中的出现频率不低于用户指定的最小支持度阈值-sequential pattern is the earliest concept of Agrawal and Srikant from the sequential pattern definitions : given a different set of sequence, in which each sequence by different elements arranged in an orderly sequence, Elements from each different project components, and given a user-specified minimum support threshold, sequential pattern mining is to find all the frequent sequences. that the sequences in the series focus on the frequency of not less than user-specified minimum threshold of support Platform: |
Size: 18715 |
Author:kiki9975 |
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Description: 序列模式的概念最早是由Agrawal和Srikant 提出的
序列模式定义：给定一个由不同序列组成的集合，其中，每个序列由不同的元素按顺序有序排列，每个元素由不同项目组成，同时给定一个用户指定的最小支持度阈值，序列模式挖掘就是找出所有的频繁子序列，即该子序列在序列集中的出现频率不低于用户指定的最小支持度阈值-sequential pattern is the earliest concept of Agrawal and Srikant from the sequential pattern definitions : given a different set of sequence, in which each sequence by different elements arranged in an orderly sequence, Elements from each different project components, and given a user-specified minimum support threshold, sequential pattern mining is to find all the frequent sequences. that the sequences in the series focus on the frequency of not less than user-specified minimum threshold of support Platform: |
Size: 18432 |
Author:kiki9975 |
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Description: 数据挖掘领域一个活跃的研究分支就是序列模式的发现，上传一个prefixspan算法-The field of data mining of an active research branch is the sequential pattern discovery algorithm to upload a PrefixSpan Platform: |
Size: 121856 |
Author:闻晞 |
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Description: 自己编的matlab程序。用于模式识别中特征的提取。是特征提取中的Sequential Forward Selection方法，简称sfs.它可以结合Maximum-Likelihood-Classifier分类器进行使用。-The matlab own procedures. For Pattern Recognition Feature Extraction. Feature Extraction is the Sequential Forward Selection method, referred to as sfs. It can be combined with Maximum-Likelihood-Classifier classifier used. Platform: |
Size: 1024 |
Author:limingxian |
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Description: 基于候选产生 测试的序列模式挖掘算法，gsp使用序列模式的向下封闭性，采用多次扫描的候选产生测试方法。-Have a test based on a candidate sequential pattern mining algorithm, gsp down the use of closed sequential patterns, and the use of multiple scan generated candidate testing methods. Platform: |
Size: 15360 |
Author:tian |
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Description: GenPrefixSpan算法源码，在PrefixSpan基础上增加了gap限制-GenPrefixSpan algorithm source code, in PrefixSpan based on an increase of gap limit Platform: |
Size: 637952 |
Author:张中举 |
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Description: 基于改进FP-Tree的序列模式挖掘算法，已经调试通过-Based on Improved FP-Tree of sequential pattern mining algorithms have been debugging through Platform: |
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Author:wanghuaqiu |
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Description: 统计模式识别工具箱（Statistical Pattern Recognition Toolbox）包含：
1，Analysis of linear discriminant function
2，Feature extraction: Linear Discriminant Analysis
3，Probability distribution estimation and clustering
4，Support Vector and other Kernel Machines-
This section should give the reader a quick overview of the methods implemented in
STPRtool.
• Analysis of linear discriminant function: Perceptron algorithm and multiclass
modification. Kozinec’s algorithm. Fisher Linear Discriminant. A collection
of known algorithms solving the Generalized Anderson’s Task.
• Feature extraction: Linear Discriminant Analysis. Principal Component Analysis
(PCA). Kernel PCA. Greedy Kernel PCA. Generalized Discriminant Analysis.
• Probability distribution estimation and clustering: Gaussian Mixture
Models. Expectation-Maximization algorithm. Minimax probability estimation.
K-means clustering.
• Support Vector and other Kernel Machines: Sequential Minimal Optimizer
(SMO). Matlab Optimization toolbox based algorithms. Interface to the
SVMlight software. Decomposition approaches to train the Multi-class SVM classifiers.
Multi-class BSVM formulation trained by Kozinec’s algorithm, Mitchell-
Demyanov-Molozenov algorithm Platform: |
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Author:查日东 |
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Description: java版的PrefixSpan算法实现，文件里包含了详细的文档说明，还有示例。-PrefixSpan algorithm. The document containing a detailed description and an example. Platform: |
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Author: |
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Description: Feature Selection using Matlab.
The DEMO includes 5 feature selection algorithms:
• Sequential Forward Selection (SFS)
• Sequential Floating Forward Selection (SFFS)
• Sequential Backward Selection (SBS)
• Sequential Floating Backward Selection (SFBS)
• ReliefF
Two CCR estimation methods:
• Cross-validation
• Resubstitution
After selecting the best feature subset, the classifier obtained can be used for classifying any pattern.
Figure: Upper panel is the pattern x feature matrix
Lower panel left are the features selected
Lower panel right is the CCR curve during feature selection steps
Right panel is the classification results of some patterns.
This software was developed using Matlab 7.5 and Windows XP.
Copyright: D. Ververidis and C.Kotropoulos
AIIA Lab, Thessaloniki, Greece,
jimver@aiia.csd.auth.gr
costas@aiia.csd.auth.gr-Feature Selection using Matlab.
The DEMO includes 5 feature selection algorithms:
• Sequential Forward Selection (SFS)
• Sequential Floating Forward Selection (SFFS)
• Sequential Backward Selection (SBS)
• Sequential Floating Backward Selection (SFBS)
• ReliefF
Two CCR estimation methods:
• Cross-validation
• Resubstitution
After selecting the best feature subset, the classifier obtained can be used for classifying any pattern.
Figure: Upper panel is the pattern x feature matrix
Lower panel left are the features selected
Lower panel right is the CCR curve during feature selection steps
Right panel is the classification results of some patterns.
This software was developed using Matlab 7.5 and Windows XP.
Copyright: D. Ververidis and C.Kotropoulos
AIIA Lab, Thessaloniki, Greece,
jimver@aiia.csd.auth.gr
costas@aiia.csd.auth.gr Platform: |
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Author:driftinwind |
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Description: 序列模式挖掘是数据挖掘的一个重要分支，在序列事务及；有关信息处理中有着广泛的应用，如顾客购物习惯、web访问模式、科学实验过程分析、自然灾害预测、疾病治疗、药物检验以及{ sizej pos；
DNA等。序列模式挖掘算法有AprioriAll、GsP、F’reeSpan、本文将设计与实现针对string数据类型的算法，来对序列模式挖掘有更深入的剖析。-Sequence pattern mining is an important branch of data mining, and in the sequence matters the information processing has a wide range of applications, such as customer shopping habits, web access mode, the process of scientific experiments, natural disaster prediction, disease treatment, drug testing, and { sizej pos DNA and so on. Sequential pattern mining algorithm AprioriAll, GsP, F' reeSpan, this paper design and implementation of algorithms for string data types, to sequence pattern mining on a more in-depth analysis. Platform: |
Size: 288768 |
Author:谢亚妮 |
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Description: 一种基于Apriori原理的算法的实现，它是序列模式挖掘中的经典算法-Apriori algorithm based on the realization of the principle, which is the classic sequential pattern mining algorithm Platform: |
Size: 133120 |
Author:张诚 |
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Search - Sequential Pattern