Type I Error
- Definition: A Type I error occurs when the model incorrectly predicts the positive class. In other words, it identifies a negative instance as positive.
- Example: If a model predicts that an email is spam (positive) when it is actually not spam (negative), this is a Type I error.
- Consequences: Type I errors can lead to unnecessary actions or consequences, such as misclassifying legitimate emails as spam, which may result in important messages being missed.