Question

Q9. While training a Neural Network, which of the following the programmer should follow: • Overfitting should be avoided for better accuracy over validation examples. • Overfitting is needed for better accuracy over validation examples • Overfitting should be avoided for better accuracy over training examples. • Overfitting is needed for better accuracy over training examples. Q10. Data used to develop a machine learning model is ____. • Test data • Hidden data • Validation data • Training data Q12. The process of adjusting the weights in ANN is known as: • Validation • Testing • Training • Activation

          Q9. While training a Neural Network, which of the following the programmer should follow:
• Overfitting should be avoided for better accuracy over validation examples.
• Overfitting is needed for better accuracy over validation examples
• Overfitting should be avoided for better accuracy over training examples.
• Overfitting is needed for better accuracy over training examples.
Q10. Data used to develop a machine learning model is ____.
• Test data
• Hidden data
• Validation data
• Training data
Q12. The process of adjusting the weights in ANN is known as:
• Validation
• Testing
• Training
• Activation

Q9. While training a Neural Network, which of the following the programmer should follow:
• Overfitting should be avoided for better accuracy over validation examples.
• Overfitting is needed for better accuracy over validation examples
• Overfitting should be avoided for better accuracy over training examples.
• Overfitting is needed for better accuracy over training examples.
Q10. Data used to develop a machine learning model is .
• Test data
• Hidden data
• Validation data
• Training data
Q12. The process of adjusting the weights in ANN is known as:
• Validation
• Testing
• Training
• Activation

Added by Jose J.

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