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Professional Machine Learning Engineer

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Topic 1 Question 60
You work for a bank and are building a random forest model for fraud detection. You have a dataset that includes transactions, of which 1% are identified as fraudulent. Which data transformation strategy would likely improve the performance of your classifier?
- Write your data in TFRecords.
- Z-normalize all the numeric features.
- Oversample the fraudulent transaction 10 times.
- Use one-hot encoding on all categorical features.
解説
Reference: https://towardsdatascience.com/how-to-build-a-machine-learning-model-to-identify-credit-card-fraud-in-5-stepsa-hands-on-modeling-5140b3bd19f1

ユーザの投票
コメント(6)
- C - https://swarit.medium.com/detecting-fraudulent-consumer-transactions-through-machine-learning-25b1f2cabbb4
  
  👍 13
  ralf_cc2021/07/09
- 正解だと思う選択肢: C
  C is the answer
  
  👍 5
  NamitSehgal2022/01/04
- 正解だと思う選択肢: C
  the best option is C
  
  👍 1
  Mohamed_Mossad2022/07/11
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