Re: Filtering methods

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Re: Filtering methods

Mark Hall

I’m not sure what you mean by “work with”, however, there are attribute evaluators in the attribute selection package that use information gain, information gain ratio and symmetric uncertainty to evaluate at merit of individual attributes.

 

https://en.wikipedia.org/wiki/Information_gain_in_decision_trees

https://en.wikipedia.org/wiki/Information_gain_ratio

https://en.wikipedia.org/wiki/Mutual_information

 

Composite variables can be used with the Weka attribute evaluators by first pre-processing the data with the CartesianProduct filter to create the composite variables.

 

Cheers,

Mark.

 

On 9/01/19, 7:55 AM, "[hidden email] on behalf of Jovani T. de Souza" <[hidden email] on behalf of [hidden email]> wrote:

 

https://mailtrack.io/trace/mail/a9dc4b50aad2b691a7671bd171dee6a35872f987.png?u=1864508

Hello guys.

 

I would like to know if it is possible to work with the joint mutual information (JMI), Conditional Mutual Information Maximization (CMIM), and fast correlation based filter (FCBF) filtering methods in Weka. If yes, how should I proceed?

 

Thanks for the informations.

 

 

Mailtrack

Remetente notificado por
Mailtrack 08/01/19 16:54:11

 


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