提问

问题如下：

In the use of machine learning (ML):

选项：

A.some techniques are termed “black box” due to data biases. B.human judgment is not needed because algorithms continuously learn from data. C.training data can be learned too precisely, resulting in inaccurate predictions when used with different datasets.

解释：

Overfitting occurs when the ML model learns the input and target dataset too precisely. In this case, the model has been “over trained” on the data and is treating noise in the data as true parameters. An ML model that has been overfitted is not able to accurately predict outcomes using a different dataset and may be too complex.