# MAE

/ˈmeɪ/ (US)

Source: https://englishreference.com/word/mae
Updated: 2026-08-08

## Senses

### 1. statistics / error measurement

noun · CEFR C1 · Technical · Academic

Stands for Mean Absolute Error. It is a way to measure how far off a set of predictions are from the actual results.

For teachers: Abbreviation for Mean Absolute Error. A metric used in statistics and machine learning to quantify the average magnitude of errors in a set of predictions, without considering their direction.

- The data scientist checked the MAE to see how well the model predicted house prices.
- By minimizing the MAE during the training phase, the researchers ensured that the model remained robust against outliers in the validation dataset.

Usage: Usually treated as an uncountable noun when referring to the method or a countable noun when referring to the specific value.

### 2. business law / contracts

noun · CEFR C2 · Technical · Formal

Stands for Material Adverse Effect. It refers to a very bad change in a company's situation that might allow a buyer to cancel a deal.

For teachers: Abbreviation for Material Adverse Effect. A legal clause in merger and acquisition agreements that allows a party to withdraw if a significant negative change occurs to the target company's business.

- The buyer tried to back out of the deal, claiming the pandemic was a MAE.
- The litigation centered on whether the sudden loss of a major patent constituted a MAE sufficient to terminate the merger agreement without penalty.

Usage: Often used within a 'MAE clause' in a contract.

### 3. female given name

noun · CEFR B2

A traditional female name, often used as a middle name.

For teachers: A female given name, historically a diminutive of Mary or Margaret.

- Her grandmother's name was Anna Mae, which was very common in that era.
- The author published her latest novel under the pseudonym Clara Mae to distinguish her fiction from her academic journals.

## Examples

- The MAE shows that our sales forecasts are usually off by five units.
- Data scientists use MAE to evaluate regression models because it is easier to interpret than squared error metrics.
- While the MAE provides a clear indication of average error magnitude, it may fail to highlight significant outliers that a root-mean-square error calculation would penalize more heavily.

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