Examtopics

AWS Certified Machine Learning - Specialty

93
95

Topic 1 Question 94
A health care company is planning to use neural networks to classify their X-ray images into normal and abnormal classes. The labeled data is divided into a training set of 1,000 images and a test set of 200 images. The initial training of a neural network model with 50 hidden layers yielded 99% accuracy on the training set, but only 55% accuracy on the test set. What changes should the Specialist consider to solve this issue?

3 つ選択
- Choose a higher number of layers
- Choose a lower number of layers
- Choose a smaller learning rate
- Enable dropout
- Include all the images from the test set in the training set
- Enable early stopping
ユーザの投票
コメント(17)
- when looking at an overfitting issue : https://www.kdnuggets.com/2019/12/5-techniques-prevent-overfitting-neural-networks.html
  
  Simplifying The Model (reduce number of layers)
  
  Early Stopping
  
  Use Data Augmentation
  
  Use Regularization (L1 + L2)
  
  Use Dropouts
  
  So looking at the options: B, D, F
  👍 46
  cnethers2021/10/13
- BDF !!!
  
  👍 8
  SophieSu2021/10/22
- BDF!!!
  
  👍 3
  Vita_Rasta844442021/10/24
シャッフルモード

93
95