Outlier Detection Demo
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Resource Overview
Detailed Documentation
This is an outlier detection demonstration program developed in MATLAB, which is highly suitable for data mining and statistical analysis applications. The program implements core outlier detection algorithms such as Z-score, Mahalanobis distance, and DBSCAN clustering methods to help users better understand and apply outlier detection principles. Through this tool, you can efficiently identify anomalies in datasets and perform corresponding analytical processing. The code includes visualization functions to plot data distribution and highlight detected outliers using different markers. Key MATLAB functions like std(), mahal(), and dbscan() are employed with customizable parameters for threshold adjustments. Whether for academic research or practical applications, this demonstration provides comprehensive guidance and robust tooling for outlier analysis. We hope you find this outlier detection demo valuable and achieve effective results in your implementations.
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