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crossovers

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This project explores an IBM telecom dataset, conducting initial EDA and data preprocessing. It examines three genetic algorithm variations for feature selection: one-point, two-point, and uniform crossover. Logistic regression is used to predict customer churn, and performance is evaluated using error bar plots.

  • Updated Jun 10, 2024
  • Jupyter Notebook

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