Description: 数据挖掘中的基于关联规则的分类算法源码2-Data Mining Association Rules based on the classification algorithm source 2 Platform: |
Size: 21088 |
Author:fansujuan |
Hits:
Description: 数据挖掘中的基于关联规则的分类算法源码3-Data Mining Association Rules based on the classification algorithm source 3 Platform: |
Size: 29460 |
Author:fansujuan |
Hits:
Description: 数据挖掘中的基于关联规则的分类算法源码4-Data Mining Association Rules based on the classification algorithm source 4 Platform: |
Size: 22573 |
Author:fansujuan |
Hits:
Description: 数据挖掘中的基于关联规则的分类算法源码5-Data Mining Association Rules based on the classification algorithm source 5 Platform: |
Size: 6135 |
Author:fansujuan |
Hits:
Description: 以从医院病案室获得的3022例数据为样本，在完成样本数据库以及糖尿病并发症的多维数据集设计后，以糖尿病并发症流行病学知识发现为重点，研究定性数据定量化挖掘模型及算法引擎的设计与实现，即将关联模型引入糖尿病并发症的流行病学研究，应用集合论中的Apriori性质，实现关联规则的挖掘引擎设计。-cases from the hospital to obtain the data for 3,022 cases samples the completion of the sample database and diabetic complications multidimensional data sets design, Complications of diabetes epidemiology knowledge discovery as the focus, Quantitative study of qualitative data mining engine model and algorithm design and implementation, Relational Model forthcoming introduction of diabetic complications epidemiological studies, the application of set theory Apriori nature, Implementation of mining association rules engine design. Platform: |
Size: 313477 |
Author:Eric Cheng |
Hits:
Description: 关联规则算法的实现和表示Delphi源码-association rules and the implementation of the algorithm source said Delphi Platform: |
Size: 701331 |
Author:clark |
Hits:
Description: 关联规则程序1
This implementation is based on the
Eclat algorithm (cfr. Zaki et al., 1997).
Several optimizations have been added such as the use of diffsets.
-an association rules procedures This implementation is based on th e Eclat algorithm (cfr. Zaki et al. , 1997). Several optimizations have been added s uch as the use of diffsets. Platform: |
Size: 4137 |
Author:lion |
Hits:
Description: 关联规则程序2
This implementation generates association rules, based on the Apriori algorithm (cfr. Agrawal et al.,1995). It takes as input a file of frequent sets in the format such as generated by the previous implementations.
-association rules 2 This implementation process generates as sociations rules, based on the Apriori algorithm (cfr. Agrawal et al. , 1995). It takes as input a file of frequent sets i n the format such as generated by the previous im plementations. Platform: |
Size: 4205 |
Author:lion |
Hits:
Description: 关联规则3
Rank-correlated set mining (Download)
This implementation is based on the rank-correlated set mining technique for numerical attributes as described in the paper \"Mining rank-correlated sets of numerical attributes\" (Calders, Goethals, Jaroszewicz, 2006).
-association rules three Rank-correlated set mining (Downlo ad) This implementation is based on the rank-co rrelated set numerical technique for mining at tributes as described in the paper "Mining rank - correlated sets of numerical attributes "(Ca lders, Goethals, Jaroszewicz, 2006). Platform: |
Size: 23050 |
Author:lion |
Hits:
Description: 关联规则4
NDI (Download)
This implementation is based on the NDI algorithm (Calders and Goethals, 2002).
Several optimizations have been added, such as a fast algorithm for the inclusion-exclusion (see Calders and Goethals, KDID 2005).
The tar-ball contains the original breadth-first implementation, but also a depth-first implementation of the basic NDI algorithm (Calders and Goethals, SDM 2005). Note, however, that this depth-first implementation does not use the generalized diffsets as described in the latter paper.
-association rules four NDI (Download) This implementation is based on the NDI algorithm (Calders and Goeth als. 2002). Several optimizations have been added, such as a fast algorithm for the inclusion - excl. usion (see Calders and Goethals. KDID 2005). The tar-ball contains the original breadth - first implementation, but also a depth-first implementation of the ba sic NDI algorithm (Calders and Goethals. SDM 2005). Note, however, that this depth-first implementation does not use the generalized diffsets as described in th e latter paper. Platform: |
Size: 12090 |
Author:lion |
Hits:
Description: 关联规则5
DIC (Download)
This implementation is based on the Dynamic Itemset Counting (DIC) algorithm (cfr. Brin et al., 1997).
The implementation contains no additional optimizations ans seems to perform worse than Apriori on almost all datasets I have tested on. All suggestions or comments are welcome.
-association rules five DIC (Download) This implementation is based on the Dynamic incremental association rule Counting (DIC) a lgorithm (cfr. domain google.stanford.edu et al. , 1997). The implementation contains no additio 44 ans optimizations seems to perform worse th Apriori on an almost all datasets I have tested o n. All suggestions or comments are welcome. Platform: |
Size: 5864 |
Author:lion |
Hits:
Description: Integration of Association Rules and Ontology for
Semantic-based Query Expansion(整合关联规则和本体语义的查询扩展)-Integration of Association Rules and POCS logy for Semantic-based Query Expansion (Integration Association Ontology rules and semantic query expansion) Platform: |
Size: 131670 |
Author:汤佩 |
Hits:
Description: Apriori算法是一个求关联规则的经典算法， 该算法可以求得一个数据库的频繁项目集-Apriori algorithm is an association rules for the classical algorithm, The algorithm can obtain a database of frequent item sets Platform: |
Size: 264882 |
Author:杨怡 |
Hits:
Description: This implementation generates association rules, based on the Apriori algorithm (cfr. Agrawal et al.,1995). It takes as input a file of frequent sets in the format such as generated by the previous implementations.
Platform: |
Size: 30447 |
Author:candy |
Hits:
Description: 一个用Apriori算法实现的数据挖掘关联规则程序-An implementation of Association Rules Data Mining using Apriori Algorithm Platform: |
Size: 85351 |
Author:潘文斌 |
Hits:
Description: 这是一个数据挖掘中的关联规则挖掘的经典算法：Apriori算法的程序-This is the code of Apriori-the classical algorithm used in Association Rules of Data Mining Platform: |
Size: 694609 |
Author:金水湾 |
Hits:
Search - association rules