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Implement a similar interface to sklearn's make_pipeline #17
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More information here : (https://www.slideshare.net/yongbangxiang/use-cases-agentmet4fof) |
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This is how the interface should look like: This is to specify the pipelines
And their candidate parameters to be grid-searched
Then connection to data, evaluator and monitor looks like this:
Lastly, to execute and log them as "Experiments" #25
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Merged
That appears to be resolved by #33 long ago. |
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Been having this in mind of viewing data analytics/ML as a workflow (which current implementation for ZEMA EMC with Haris Lulic is kind-of adopting already), that is a sequence of functions applied one after the other.
sklearn reference
Example:
group_of_agents = make_pipeline(FFT(), PCA(pca_parameters), LDA(lda_parameters))
fit
andtransform
similar to how sklearn structures its classesThe advantage with the agent network architecture:
Example:
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