DeleteAnomalies

DeleteAnomalies[{example1,example2,}]

gives a list in which examplei that are considered anomalous have been dropped.

DeleteAnomalies[fun,data]

drops anomalies in data using the given AnomalyDetectorFunction[] or LearnedDistribution[].

Details and Options

Examples

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Basic Examples  (3)

Drop anomalous examples in a numeric dataset:

Delete anomalous examples in a nominal dataset:

Delete anomalies from a list of colors:

Scope  (2)

Train an AnomalyDetectorFunction on a two-dimensional array of pseudorandom real numbers:

Use the trained AnomalyDetectorFunction with DeleteAnomalies to drop anomalous examples:

Obtain a random sample of training and test datasets of images:

Add anomalous examples to corrupt the datasets:

Train a distribution on images:

Use the trained distribution to drop anomalous examples in the test set:

Options  (2)

AcceptanceThreshold  (1)

Specify the AcceptanceThreshold for dropping anomalies from a list of colors:

Method  (1)

Create a dataset sampled from two different distributions:

Delete anomalies in the dataset using the "Multinormal" method:

Delete anomalies in the dataset using the "KernelDensityEstimation" method:

Applications  (4)

Find the statistical mean of numeric values with an anomaly:

Plot a list of numeric values that contains anomalies:

Plot a list of numeric values after removing anomalies:

Delete anomalies before computing the mean:

Find the linear fit for numerical data:

Delete outliers before modeling the fit:

Obtain a dataset of images:

Train an anomaly detector on the training set:

Drop anomalous examples in the test set:

Wolfram Research (2019), DeleteAnomalies, Wolfram Language function, https://reference.wolfram.com/language/ref/DeleteAnomalies.html (updated 2020).

Text

Wolfram Research (2019), DeleteAnomalies, Wolfram Language function, https://reference.wolfram.com/language/ref/DeleteAnomalies.html (updated 2020).

BibTeX

@misc{reference.wolfram_2021_deleteanomalies, author="Wolfram Research", title="{DeleteAnomalies}", year="2020", howpublished="\url{https://reference.wolfram.com/language/ref/DeleteAnomalies.html}", note=[Accessed: 04-August-2021 ]}

BibLaTeX

@online{reference.wolfram_2021_deleteanomalies, organization={Wolfram Research}, title={DeleteAnomalies}, year={2020}, url={https://reference.wolfram.com/language/ref/DeleteAnomalies.html}, note=[Accessed: 04-August-2021 ]}

CMS

Wolfram Language. 2019. "DeleteAnomalies." Wolfram Language & System Documentation Center. Wolfram Research. Last Modified 2020. https://reference.wolfram.com/language/ref/DeleteAnomalies.html.

APA

Wolfram Language. (2019). DeleteAnomalies. Wolfram Language & System Documentation Center. Retrieved from https://reference.wolfram.com/language/ref/DeleteAnomalies.html