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q2-adapative-branching

Quarter 2 Project for the TJHSST ML 1 class. Completed by Leah Zhang and Victoria Zhang. The project investigates a novel constrained optimization approach to optimizing decision trees against overfitting, testing the additional search metaheuristics of simulated annealing and differential equation gradients on improving the model.

In this repository we have three folders: data, deliverables, and models.

  1. data: this holds all the data we used e.g. credit_risk.csv
  2. deliverables: here is our paper and presentation both in PDF and powerpoint form
  3. models: finally here is our 5 models baseline_tree, diffeq_balance_tree, hybrid_SA_unbalanced, modified_tree, and random_forest. Find out more through our paper in the deliverables folder.

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Quarter 2 Project for the TJHSST ML 1 class. Completed by Leah Zhang and Victoria Zhang. The project investigates a novel constrained optimization approach to optimizing decision trees against overfitting, testing the additional search metaheuristics of simulated annealing and differential equation gradients on improving the model.

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