麻烦解答一下

问题如下：

Achler has the data ready for the model training process. Rivera asks Achler to include start-up failure rates as a feature. Achler notices that the number of start-ups that fail (majority class) is significantly larger than the number of the start-ups that are successful (minority class).

Achler is concerned that because of class imbalance, the model will not be able to discriminate between start-ups that fail and start-ups that are successful.

Achler’s model training concern related to the model’s ability to discriminate could be addressed by randomly:

选项：

oversampling the failed start-up data

oversampling the successful start-up data

undersampling the successful start-up data

解释：

B is correct.

Achler is concerned about class imbalance, which can be resolved by balancing the training data. The majority class (the failed start-up data) can be randomly undersampled, or the minority class (the successful start-up data) can be randomly oversampled.

考点：Model Training: Model Selection