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CAR EVALUATION

Machine Learning. CAR EVALUATION. Rashid Lepshokov Nikolay Pukhovskiy Halden 2011. Dataset (input). Dataset (target). Dataset. Neural Network Configuration. Target/Output correlation. Training algorithms. Levenberg-Marquardt BFGS Quasi-Newton Resilient Backpropagation.

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CAR EVALUATION

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  1. Machine Learning CAR EVALUATION Rashid Lepshokov Nikolay Pukhovskiy Halden 2011

  2. Dataset(input)

  3. Dataset (target)

  4. Dataset

  5. Neural Network Configuration

  6. Target/Output correlation

  7. Training algorithms • Levenberg-Marquardt • BFGS Quasi-Newton • ResilientBackpropagation

  8. Levenberg-Marquardt

  9. BFGS Quasi-Newton

  10. Resilient Backpropagation

  11. Results and comparison Error rate: C5.0 – 37% NNT – 0.25% • Levenberg-Marquardt • Number of neurons in the hidden layer 20 • Correlation between outputs and targets for test data is equal to 9.7 • Mean Squared Error is equal to 0,03 • 23 iterations. Thank you for attention!!!

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