e-XpertSolutions/go-iforest
Isolation forest implementation in Go
This tool helps you automatically identify unusual or abnormal data points within your datasets. You provide your raw numerical data, and it tells you which data points are likely anomalies. This is useful for anyone who needs to spot outliers in their data, such as fraud analysts, quality control inspectors, or system administrators monitoring sensor data.
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Use this if you have a dataset where normal patterns are abundant, but you need to quickly flag rare, suspicious, or unexpected observations without predefined anomaly examples.
Not ideal if you already have labeled examples of both normal and anomalous data, as this tool is designed for unsupervised anomaly detection.
Stars
39
Forks
8
Language
Go
License
BSD-3-Clause
Category
Last pushed
Nov 29, 2022
Commits (30d)
0
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