# Type I Error

## Definition of Type I Error

Type I error: A type I error, also known as a false positive error, is the incorrect rejection of a true null hypothesis.

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# Type I Error

## Definition of Type I Error

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## Similar Posts

### Natural Language Processing (NPL)

### Normalized

### Ensembling

### Covariance

### Windowed Aggregation

Type I error: A type I error, also known as a false positive error, is the incorrect rejection of a true null hypothesis.

ByDavis

Definition of Natural Language Processing (NPL) Natural Language Processing (NPL): Natural language processing (NLP) is a field of computer science and linguistics that deals with the interaction between computers and human languages, and with the development of software that can understand natural language.

ByDavis

Definition of Normalized Normalized: Normalized is a statistic term referring to the process of adjusting a value to have a unit of measurement. For example, the value of weight can be normalized by dividing it by the unit of weight, such as kilograms.

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Definition of Ensembling Ensembling: Ensembling is a technique used in machine learning that consists of combining the predictions of multiple models in order to improve the accuracy of the predictions. What is Ensembling used for? Ensembling is a technique in data science and machine learning in which multiple prediction models are combined to produce a…

ByDavis

Covariance is a measure of how two variables change together. It is calculated as the variance of the product of the two variables divided by the product of their standard deviations.

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Definition of Windowed Aggregation Windowed Aggregation: Windowed aggregation is the process of computing a statistic over a fixed-size window of data. The window slides along the data set, taking a fixed number of values from the start of the set and computing the statistic for each one. This can be done with any type of…