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predictiveApriori from group nz.ac.waikato.cms.weka (version 1.0.4)

Class implementing the predictive apriori algorithm for mining association rules. It searches with an increasing support threshold for the best 'n' rules concerning a support-based corrected confidence value. For more information see: Tobias Scheffer: Finding Association Rules That Trade Support Optimally against Confidence. In: 5th European Conference on Principles of Data Mining and Knowledge Discovery, 424-435, 2001.

Group: nz.ac.waikato.cms.weka Artifact: predictiveApriori
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Download predictiveApriori.jar (1.0.4)
 

2 downloads

predictiveApriori from group nz.ac.waikato.cms.weka (version 1.0.3)

Class implementing the predictive apriori algorithm for mining association rules. It searches with an increasing support threshold for the best 'n' rules concerning a support-based corrected confidence value. For more information see: Tobias Scheffer: Finding Association Rules That Trade Support Optimally against Confidence. In: 5th European Conference on Principles of Data Mining and Knowledge Discovery, 424-435, 2001.

Group: nz.ac.waikato.cms.weka Artifact: predictiveApriori
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Download predictiveApriori.jar (1.0.3)
 

2 downloads

predictiveApriori from group nz.ac.waikato.cms.weka (version 1.0.2)

Class implementing the predictive apriori algorithm for mining association rules. It searches with an increasing support threshold for the best 'n' rules concerning a support-based corrected confidence value. For more information see: Tobias Scheffer: Finding Association Rules That Trade Support Optimally against Confidence. In: 5th European Conference on Principles of Data Mining and Knowledge Discovery, 424-435, 2001.

Group: nz.ac.waikato.cms.weka Artifact: predictiveApriori
Show documentation Show source 
Download predictiveApriori.jar (1.0.2)
 

2 downloads

predictiveApriori from group nz.ac.waikato.cms.weka (version 1.0.1)

Class implementing the predictive apriori algorithm for mining association rules. It searches with an increasing support threshold for the best 'n' rules concerning a support-based corrected confidence value. For more information see: Tobias Scheffer: Finding Association Rules That Trade Support Optimally against Confidence. In: 5th European Conference on Principles of Data Mining and Knowledge Discovery, 424-435, 2001.

Group: nz.ac.waikato.cms.weka Artifact: predictiveApriori
Show documentation Show source 
Download predictiveApriori.jar (1.0.1)
 

2 downloads



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