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KI-Glossar

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IQR Method

Non-parametric technique identifying outliers as those located outside 1.5 times the interquartile range above the third quartile or below the first.

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Grubbs' Test

Statistical hypothesis test identifying univariate outliers by assuming a normal distribution and testing whether the extreme value is significantly different.

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Connectivity-Based Outlier Factor

Measure based on the connectivity of k-nearest neighbors assessing the degree of isolation of a point relative to the overall structure of the neighborhood graph.

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Angle-Based Outlier Detection

Method exploiting angular properties between points in the data space, where anomalies exhibit lower angular variances than normal points.

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Histogram-Based Outlier Score

Multidimensional histogram-based approach evaluating the rarity of an observation based on the frequency of the histogram cells it occupies.

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k-NN Outlier Detection

Method using the distance to k-nearest neighbors as an anomaly score, where points with the highest average distances are considered outliers.

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Subspace Outlier Detection

Technique identifying anomalies in different dimensional subspaces where they may be more detectable than in the full dimensional space.

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Feature Bagging

Ensemble method creating multiple detectors on different random subsets of features, aggregating their results to improve detection robustness.

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PCA Anomaly Detection

Use of principal component analysis to detect anomalies as points with high reconstruction scores after projection onto principal components.

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