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bhroben/Feature-importance-methods-of-simulated-binary-black-holes

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Feature-importance-methods-of-simulated-binary-black-holes

In our work we studied almost 2 million simulations of binary stellar systems, carried out with the rapid-synthesis binary population code MOBSE, searching for the most important features that determine the eventual evolution of a binary stellar system into a merging BBH, source of GWs.

The Goal of the project is to find what features have the highest impact on the evolution of a binary system into a Binary Black Hole. To do this we implemented four methods:

  • Weights of linear SVM
  • Medium Difference in Impurity for RFC
  • Permutation importance
  • Feature dropping

We also used SHAP values. We draw our conclusions in the project presentation.

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Feature importance methods for Black Holes Dataset

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