kmeans module¶
A k-means classification of the optimization history.
- class gemseo.post.kmeans.KMeans(opt_problem)[source]
Bases:
OptPostProcessor
Performs a k-means clustering on optimization history.
The default number of clusters is 5 and can be modified in option.
The k-means construction depends on the
MiniBatchKMeans
class of thecluster
module of the scikit-learn library .- Parameters:
opt_problem (OptimizationProblem) – The optimization problem to be post-processed.
- Raises:
ValueError – If the JSON grammar file for the options of the post-processor does not exist.
- database: Database
The database generated by the optimization problem.
- materials_for_plotting: dict[Any, Any]
The materials to eventually rebuild the plot in another framework.
- opt_problem: OptimizationProblem
The optimization problem.