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Glossario IA

Il dizionario completo dell'Intelligenza Artificiale

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Random Decision Tree

Tree structure generated randomly where each node splits the feature space according to a random cut, creating partitions that progressively isolate observations.

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Anomaly Score

Quantitative metric calculated from the path length in the tree, indicating the degree of abnormality of an observation where a high score corresponds to a high probability of being an anomaly.

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Isolation Path

Number of splits needed from the root to the leaf containing an observation, where anomalies present significantly shorter paths than normal points.

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Contamination Factor

Crucial parameter estimating the expected proportion of anomalies in the dataset, generally between 0.01 and 0.1, influencing the classification threshold.

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Average Path Length

Theoretical expected value of the isolation path for unstructured data, used as reference to normalize anomaly scores in the final calculation.

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Random Feature Split

Random selection of a feature and a split value at each node, avoiding biases related to feature distributions and favoring the isolation of anomalies.

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Normality Score

Transformation of the anomaly score on a normalized scale, often between 0 and 1, facilitating interpretation and comparison between different models or datasets.

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Point Anomaly

Individual observation that deviates significantly from the expected behavior of the data, easily identifiable by its short isolation path length in the algorithm.

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Recursive partitioning

Iterative process of dividing the data space into progressively smaller sub-regions, creating a hierarchical structure that effectively isolates outlier observations.

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Detection threshold

Cut-off value determined by the contamination factor separating normal observations from anomalies, calculated from the distribution of anomaly scores on the dataset.

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Bounding box

Multidimensional hyper-rectangle created at each tree split, defining the partition's boundaries and allowing for efficient calculation of isolation paths.

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Local Outlier Factor

Alternative anomaly detection metric based on local density, often compared to Isolation Forest to evaluate performance on different types of data distributions.

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Tree pruning

Technique for limiting tree growth by stopping the split when nodes contain a single sample or reach the maximum depth, optimizing computation times.

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