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Outlier Detection Using Minimum Vector Variance Algorithm with Depth Function and Mahalanobis Distance
2021
Jurnal Matematika Statistika dan Komputasi
Outliers are observations where the point of observation deviates from the data pattern. The existence of outliers in the data can cause irregularities in the results of data analysis. One solution to this problem is to detect outliers using a statistical approach. The statistical approach method used in this study is the Minimum Vector Variance (MVV) algorithm which has robust characteristics for outliers. The purpose of this research is to detect outliers using the MVV algorithm by changing
doi:10.20956/j.v17i3.12629
fatcat:bmre4drgovc2lfi4r37i4kpnyu