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Isolation Forest is an unsupervised anomaly detection algorithm for outlier detection that uses random decision trees (iTrees) and data isolation and in the field of machine learning. It computes an anomaly score based on average path length—shorter path length = anomalies, making it efficient and scalable for high-dimensional datasets ...
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