# Type II Error

## Definition of Type II Error

Type II error: A type II error, also known as a false negative error, is the incorrect acceptance of a false null hypothesis.

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# Type II Error

## Definition of Type II Error

*Related*

## Similar Posts

### Zero-Sum Game

### Moving Average

### Feature Selection

### Objective Function

### Absolute Error

Type II error: A type II error, also known as a false negative error, is the incorrect acceptance of a false null hypothesis.

ByDavis

Definition of Zero-Sum Game Zero-Sum Game: In game theory, a zero-sum game is a mathematical model of a situation in which each participant’s gain or loss of utility is exactly balanced by the losses or gains of the other participants. If the total gains from the interactions of all participants are net zero change, then…

ByDavis

Definition of Moving Average A moving average (MA) is a statistical measure that calculates the average value of a given set of data points over a designated amount of time. The MA is typically used to smooth out irregularities or fluctuations in the data and to help identify trends. The most common type of MA…

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Definition of Feature Selection Feature Selection: Feature selection is the process of choosing which features (or attributes) of a data set to use in order to solve a problem. This is an important step in data science, as it can help reduce the complexity of a problem and improve the accuracy of predictions or models….

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Definition of Objective Function An objective function (in machine learning) is a mathematical formula used to calculate the relative merit of each possible solution to a problem. The objective function takes into account the inputs and outputs of a problem, as well as any constraints that may exist. It then calculates a score for each…

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Absolute Error is the difference between the predicted value and the actual value.