Auto weka VS baysian optimization

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Auto weka VS baysian optimization

asadbtk
For instance, if we want to perform hyperparameter optimization in r language using baysian optimization, is it the same as we do optimization using auto weka?

Best regards 

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Re: Auto weka VS baysian optimization

Eibe Frank-3
The main difference is probably that Auto-WEKA also searches through a subset of possible learning algorithms and does not just do hyperparameter tuning Additionally, it considers using attribute selection schemes in conjunction with the learning algorithm.

Cheers,
Eibe

On Fri, Dec 27, 2019 at 2:35 PM javed khan <[hidden email]> wrote:
For instance, if we want to perform hyperparameter optimization in r language using baysian optimization, is it the same as we do optimization using auto weka?

Best regards 
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Re: Auto weka VS baysian optimization

asadbtk
Hi Eibe, but when we already selects a dataset and learning algorithm (random forest), I think the auto weka then selects the parameters of only that learning algorithm? 

Best regards 

On Friday, December 27, 2019, Eibe Frank <[hidden email]> wrote:
The main difference is probably that Auto-WEKA also searches through a subset of possible learning algorithms and does not just do hyperparameter tuning Additionally, it considers using attribute selection schemes in conjunction with the learning algorithm.

Cheers,
Eibe

On Fri, Dec 27, 2019 at 2:35 PM javed khan <[hidden email]> wrote:
For instance, if we want to perform hyperparameter optimization in r language using baysian optimization, is it the same as we do optimization using auto weka?

Best regards 
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Re: Auto weka VS baysian optimization

Eibe Frank
AFAIK, the Auto-WEKA package does not permit specification of a particular learning algorithm for optimisation.

Cheers,
Eibe

On Sat, Dec 28, 2019 at 1:17 AM javed khan <[hidden email]> wrote:
Hi Eibe, but when we already selects a dataset and learning algorithm (random forest), I think the auto weka then selects the parameters of only that learning algorithm? 

Best regards 

On Friday, December 27, 2019, Eibe Frank <[hidden email]> wrote:
The main difference is probably that Auto-WEKA also searches through a subset of possible learning algorithms and does not just do hyperparameter tuning Additionally, it considers using attribute selection schemes in conjunction with the learning algorithm.

Cheers,
Eibe

On Fri, Dec 27, 2019 at 2:35 PM javed khan <[hidden email]> wrote:
For instance, if we want to perform hyperparameter optimization in r language using baysian optimization, is it the same as we do optimization using auto weka?

Best regards 
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Re: Auto weka VS baysian optimization

asadbtk
Yes Eibe, I realized that later. The confusion came because I selected a dataset, then selected a classifier to random forest and then run auto weka and it selected random forest as a final model. But for another dataset when again I selected random forest, auto weka selected linear regression. 

Best regards and happy new year. 

On Wednesday, January 1, 2020, Eibe Frank <[hidden email]> wrote:
AFAIK, the Auto-WEKA package does not permit specification of a particular learning algorithm for optimisation.

Cheers,
Eibe

On Sat, Dec 28, 2019 at 1:17 AM javed khan <[hidden email]> wrote:
Hi Eibe, but when we already selects a dataset and learning algorithm (random forest), I think the auto weka then selects the parameters of only that learning algorithm? 

Best regards 

On Friday, December 27, 2019, Eibe Frank <[hidden email]> wrote:
The main difference is probably that Auto-WEKA also searches through a subset of possible learning algorithms and does not just do hyperparameter tuning Additionally, it considers using attribute selection schemes in conjunction with the learning algorithm.

Cheers,
Eibe

On Fri, Dec 27, 2019 at 2:35 PM javed khan <[hidden email]> wrote:
For instance, if we want to perform hyperparameter optimization in r language using baysian optimization, is it the same as we do optimization using auto weka?

Best regards 
_______________________________________________
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