Isolation Forest detects anomalies by isolating observations. It builds binary trees (called iTrees) by recursively partitioning the data using random split thresholds. Since anomalies are easier to ...

Multivariate time series (MTS) clustering is an important technique for discovering co-evolving patterns and interpreting group characteristics in many areas including economics, bioinformatics, data ...

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Incomplete time series data is a common problem in real-world application scenarios. Recent research has taken the approach of separating interpolation and anomaly detection, which is not interactive ...