Topic 1 Question 339
A banking company provides financial products to customers around the world. A machine learning (ML) specialist collected transaction data from internal customers. The ML specialist split the dataset into training, testing, and validation datasets. The ML specialist analyzed the training dataset by using Amazon SageMaker Clarify. The analysis found that the training dataset contained fewer examples of customers in the 40 to 55 year-old age group compared to the other age groups.
Which type of pretraining bias did the ML specialist observe in the training dataset?
Difference in proportions of labels (DPL)
Class imbalance (CI)
Conditional demographic disparity (CDD)
Kolmogorov-Smirnov (KS)
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- 正解だと思う選択肢: B
The type of pretraining bias observed in the training dataset, where there are fewer examples of customers in the 40 to 55 year-old age group compared to the other age groups, is:
B. Class imbalance (CI)
Explanation: Class imbalance (CI) refers to a situation where certain classes or groups are underrepresented in the dataset. In this case, the age group 40 to 55 is underrepresented compared to other age groups. Difference in proportions of labels (DPL) generally refers to differences in the proportions of different labels (outcomes) rather than input features like age. Conditional demographic disparity (CDD) refers to differences in outcomes for different demographic groups conditional on certain factors, not the raw distribution of demographic features. Kolmogorov-Smirnov (KS) is a statistical test used to compare distributions, but it is not specifically a type of bias. Therefore, the correct answer is B. Class imbalance (CI).
👍 2Shivanshub2024/08/31 - 正解だと思う選択肢: B
Class imbalance can lead to biased models that perform poorly on the underrepresented class or group, as the model may not have enough examples to learn the patterns and characteristics of that class effectively.
👍 1GS_772024/08/30 - 正解だと思う選択肢: C
Answer is C
👍 1aragon_saa2024/08/30
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