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kategorie
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podkategorie
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pojęcia
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pojęcia

Multivariate anomaly

Statistically abnormal observation detected by simultaneously analyzing relationships and interactions between multiple variables, where each variable individually may appear normal.

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Variational autoencoder

Probabilistic neural network that learns the latent distribution of normal data and detects anomalies by their low probability under this learned distribution.

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Robust covariance matrix

Statistical estimator resistant to extreme values, calculating relationships between variables while minimizing the influence of anomalies on the estimation.

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Hotelling's T-squared

Multivariate statistic generalizing the t-student test, measuring the distance of an observation to the distribution center while accounting for the covariance structure.

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Gaussian Mixture Model (GMM)

Probabilistic model representing data as a combination of multiple Gaussian distributions, where low probabilities indicate abnormal observations.

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Multivariate DBSCAN

Density-based clustering algorithm identifying anomalies as points not belonging to any dense cluster in multidimensional space.

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Isolation Map

Multidimensional visualization technique preserving local relationships to help visually identify clusters and anomalies in complex data.

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Robust PCA

Variant of principal component analysis resistant to anomalies, separating data into low-rank subspace and sparse matrix of anomalies.

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Copula-based detection

Method that models the dependency structure between variables independently of their marginal distributions to detect multivariate anomalies.

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Minimum Covariance Determinant (MCD)

Robust estimator that finds the subset of observations with the minimum covariance determinant, providing an estimate resistant to extreme values.

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