From: STAR_outliers: a python package that separates univariate outliers from non-normal distributions
Algorithm | Algorithm type | Description |
---|---|---|
IF | IF | IF out of the box model |
IF-calibrated | IF | IF calibrated to remove as many outliers as STAR_outliers |
STAR | STAR_outliers | STAR_outliers |
[3] (p = 90) | [3] | [3] using percentiles 90 and 10 to estimate Tukey-gh parameters |
[3] (p = 91) | [3] | [3] using percentiles 91 and 9 to estimate Tukey-gh parameters |
[3] (p = 92) | [3] | [3] using percentiles 92 and 8 to estimate Tukey-gh parameters |
[3] (p = 93) | [3] | [3] using percentiles 93 and 7 to estimate Tukey-gh parameters |
[3] (p = 94) | [3] | [3] using percentiles 94 and 6 to estimate Tukey-gh parameters |
[3] (p = 95) | [3] | [3] using percentiles 95 and 5 to estimate Tukey-gh parameters |
[3] (p = 96) | [3] | [3] using percentiles 96 and 4 to estimate Tukey-gh parameters |
[3] (p = 97) | [3] | [3] using percentiles 97 and 3 to estimate Tukey-gh parameters |
[3] (p = 98) | [3] | [3] using percentiles 98 and 2 to estimate Tukey-gh parameters |
[3] (p = 99) | [3] | [3] using percentiles 99 and 1 to estimate Tukey-gh parameters |
T2 | [9] | T2 with 2 iterations |
T2_yj | [9] | T2 with 2 iterations for yj transformed data |
T3 | [9] | T2 with 3 iterations |
T3_yj | [9] | T2 with 3 iterations for yj transformed data |
T4 | [9] | T2 with 4 iterations |
T4_yj | [9] | T2 with 4 iterations for yj transformed data |
3SD | normal | standard 3SD cutoff |
3SD_yj | normal | 3SD cutoff for yj transformed data |
IQR | normal | standard IQR cutoff |
IQR_yj | normal | standard IQR cutoff for yj transformed data |
MAD | normal | standard MAD cutoff |
MAD_yj | normal | standard MAD cutoff for yj transformed data |