Different algorithm for modeling and nested in GA for feature selection

Hi,

 

can you maybe post your proess?

 

~Martin

Sure

 

 

Dear lattii,

 

to be honest your process looks a bit odd in general. You apply the k-nn on the learned data in the GA, which leads to overtraining. Further you used a split validation by hand w/o taking the Ga into account, this is again something which yields to overtraining. I would suggest to put a cross validation around everything. It is further a bit strange to use a naive bayes to generate features and a k-NN for classification - but if it works, it works.

 

~Martin

thanks for your guidance,

Do you think if I delete the whole K-NN process in GA and then bring the modeling process in GA (delete the splitting operator and using split validation), it work true ?

and about the model discussed, you are saying if my model works, so it is true. In this case the feature selection is done using K-NN or NB ? I get a little confused. I am new user to RM, so sorry for these questions.