rule generation in a big dataset Announcing the arrival of Valued Associate #679: Cesar Manara Planned maintenance scheduled April 17/18, 2019 at 00:00UTC (8:00pm US/Eastern) 2019 Moderator Election Q&A - Questionnaire 2019 Community Moderator Election ResultsSequence pattern mining on continuous datasetWhat is the relationship between clustering and association rule mining?Association rule mining interpretationMapping xml tags by Rule Learning/Generation AlgorithmsAssociation Rule Learning for Home Electricity or Water Data?Can inferencing come from incomplete rule sets?Categorical data with order and blanks, is frequent dataset or k-modes a better option?How is FP-Tree used in FP-Growth maintained for large datasetSequence extraction in a dataset

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rule generation in a big dataset



Announcing the arrival of Valued Associate #679: Cesar Manara
Planned maintenance scheduled April 17/18, 2019 at 00:00UTC (8:00pm US/Eastern)
2019 Moderator Election Q&A - Questionnaire
2019 Community Moderator Election ResultsSequence pattern mining on continuous datasetWhat is the relationship between clustering and association rule mining?Association rule mining interpretationMapping xml tags by Rule Learning/Generation AlgorithmsAssociation Rule Learning for Home Electricity or Water Data?Can inferencing come from incomplete rule sets?Categorical data with order and blanks, is frequent dataset or k-modes a better option?How is FP-Tree used in FP-Growth maintained for large datasetSequence extraction in a dataset










1












$begingroup$


Given a dataset with 30 fields and 25000 instances,



1) what are your suggestions for novel methods of rule extraction?



2) Can I use association rule mining in addition to sequential rule mining?



3) which method can be more appropriate for such a big dataset?Apriori-based like SPIRIT, SPADE, SPAM, IBM or pattern growth ones like FreeSpan, PrefixSpan, SLPMiner?



*the output field (risk) is labelled as very low, low, medium, high, very high. Also, there is a temporal field (date) for each instance. An example is given below.



$$
beginarrayc
hline
mathbfdate& mathbftemperature & mathbfdensity & mathbfrisk \ hline
2018/1/2 & 15 & 100 & textvery high\ hline
& & &\
endarray
$$










share|improve this question











$endgroup$











  • $begingroup$
    Hi Anna, What do you mean by novel? There are methods to extract rules, yes. Without any given target variable you could use both methods to find correlations in the dataset.
    $endgroup$
    – S van Balen
    Apr 1 at 22:15










  • $begingroup$
    Hi Balen, by the novel, I meant, for example, using deep neural networks or those that can work with my large dataset.
    $endgroup$
    – anna
    Apr 2 at 17:08















1












$begingroup$


Given a dataset with 30 fields and 25000 instances,



1) what are your suggestions for novel methods of rule extraction?



2) Can I use association rule mining in addition to sequential rule mining?



3) which method can be more appropriate for such a big dataset?Apriori-based like SPIRIT, SPADE, SPAM, IBM or pattern growth ones like FreeSpan, PrefixSpan, SLPMiner?



*the output field (risk) is labelled as very low, low, medium, high, very high. Also, there is a temporal field (date) for each instance. An example is given below.



$$
beginarrayc
hline
mathbfdate& mathbftemperature & mathbfdensity & mathbfrisk \ hline
2018/1/2 & 15 & 100 & textvery high\ hline
& & &\
endarray
$$










share|improve this question











$endgroup$











  • $begingroup$
    Hi Anna, What do you mean by novel? There are methods to extract rules, yes. Without any given target variable you could use both methods to find correlations in the dataset.
    $endgroup$
    – S van Balen
    Apr 1 at 22:15










  • $begingroup$
    Hi Balen, by the novel, I meant, for example, using deep neural networks or those that can work with my large dataset.
    $endgroup$
    – anna
    Apr 2 at 17:08













1












1








1





$begingroup$


Given a dataset with 30 fields and 25000 instances,



1) what are your suggestions for novel methods of rule extraction?



2) Can I use association rule mining in addition to sequential rule mining?



3) which method can be more appropriate for such a big dataset?Apriori-based like SPIRIT, SPADE, SPAM, IBM or pattern growth ones like FreeSpan, PrefixSpan, SLPMiner?



*the output field (risk) is labelled as very low, low, medium, high, very high. Also, there is a temporal field (date) for each instance. An example is given below.



$$
beginarrayc
hline
mathbfdate& mathbftemperature & mathbfdensity & mathbfrisk \ hline
2018/1/2 & 15 & 100 & textvery high\ hline
& & &\
endarray
$$










share|improve this question











$endgroup$




Given a dataset with 30 fields and 25000 instances,



1) what are your suggestions for novel methods of rule extraction?



2) Can I use association rule mining in addition to sequential rule mining?



3) which method can be more appropriate for such a big dataset?Apriori-based like SPIRIT, SPADE, SPAM, IBM or pattern growth ones like FreeSpan, PrefixSpan, SLPMiner?



*the output field (risk) is labelled as very low, low, medium, high, very high. Also, there is a temporal field (date) for each instance. An example is given below.



$$
beginarrayc
hline
mathbfdate& mathbftemperature & mathbfdensity & mathbfrisk \ hline
2018/1/2 & 15 & 100 & textvery high\ hline
& & &\
endarray
$$







association-rules sequential-pattern-mining






share|improve this question















share|improve this question













share|improve this question




share|improve this question








edited Apr 2 at 17:12







anna

















asked Apr 1 at 14:56









annaanna

63




63











  • $begingroup$
    Hi Anna, What do you mean by novel? There are methods to extract rules, yes. Without any given target variable you could use both methods to find correlations in the dataset.
    $endgroup$
    – S van Balen
    Apr 1 at 22:15










  • $begingroup$
    Hi Balen, by the novel, I meant, for example, using deep neural networks or those that can work with my large dataset.
    $endgroup$
    – anna
    Apr 2 at 17:08
















  • $begingroup$
    Hi Anna, What do you mean by novel? There are methods to extract rules, yes. Without any given target variable you could use both methods to find correlations in the dataset.
    $endgroup$
    – S van Balen
    Apr 1 at 22:15










  • $begingroup$
    Hi Balen, by the novel, I meant, for example, using deep neural networks or those that can work with my large dataset.
    $endgroup$
    – anna
    Apr 2 at 17:08















$begingroup$
Hi Anna, What do you mean by novel? There are methods to extract rules, yes. Without any given target variable you could use both methods to find correlations in the dataset.
$endgroup$
– S van Balen
Apr 1 at 22:15




$begingroup$
Hi Anna, What do you mean by novel? There are methods to extract rules, yes. Without any given target variable you could use both methods to find correlations in the dataset.
$endgroup$
– S van Balen
Apr 1 at 22:15












$begingroup$
Hi Balen, by the novel, I meant, for example, using deep neural networks or those that can work with my large dataset.
$endgroup$
– anna
Apr 2 at 17:08




$begingroup$
Hi Balen, by the novel, I meant, for example, using deep neural networks or those that can work with my large dataset.
$endgroup$
– anna
Apr 2 at 17:08










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