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AI-Advisor Point Anomaly Detection

This algorithm detects anomaly points for continuous univariate time series that peaks up suddenly, using unsupervised machine learning.

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About

This algorithm is a technique for detecting unusual patterns that differ from common patterns in a data set, and considers individual data points as outliers when they differ significantly from surrounding data. Various machine learning algorithms can find outliers that match the algorithm's characteristics, and they learn to receive higher scores as the distance between the distribution of normal data and the distribution of abnormal data increases, and as the proportion of abnormal data decreases. The machine learning algorithm with the highest final score is selected, and the parameters optimized for it are determined.

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