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runtime-comparisons

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EofK / Benchmark-16-ML-Models-Using-the-Dry-Bean-Dataset

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This project analyzed and compared the performance of 16 machine learning models on a supervised classification task using the Dry Bean dataset. This project pursued two objectives: (1) Measure how accurately each model classifies unseen bean samples, and (2) Determine each model’s runtime for its classification training and testing process.

benchmark machine-learning classification hyperparameter-tuning feature-correlation dry-bean-dataset runtime-comparisons benchmark-models
  • Updated Aug 4, 2025
  • Jupyter Notebook

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