Why is my LOF algorithm producing the opposite result it should?
$begingroup$
What could cause the local outlier factor (LOF) to output below 1.0 for outliers and above 1.0 for inliers? I have my code sort of working just by inverting the output, but I can't figure out what's wrong with my algorithm. I'm following the one Wikipedia lists to the letter, but for some reason, it's producing the opposite result.
On a high, non-code-specific level, does anyone know what could cause the algorithm to behave like this? I've looked everywhere in the code, and to the best of my knowledge, it's doing exactly what this describes.
clustering anomaly-detection outlier
asked 2 hours ago
ZayaZaya
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add a comment |
$begingroup$
What could cause the local outlier factor (LOF) to output below 1.0 for outliers and above 1.0 for inliers? I have my code sort of working just by inverting the output, but I can't figure out what's wrong with my algorithm. I'm following the one Wikipedia lists to the letter, but for some reason, it's producing the opposite result.
On a high, non-code-specific level, does anyone know what could cause the algorithm to behave like this? I've looked everywhere in the code, and to the best of my knowledge, it's doing exactly what this describes.
clustering anomaly-detection outlier
asked 2 hours ago
ZayaZaya
101
New contributor
Zaya is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
$begingroup$
What could cause the local outlier factor (LOF) to output below 1.0 for outliers and above 1.0 for inliers? I have my code sort of working just by inverting the output, but I can't figure out what's wrong with my algorithm. I'm following the one Wikipedia lists to the letter, but for some reason, it's producing the opposite result.
On a high, non-code-specific level, does anyone know what could cause the algorithm to behave like this? I've looked everywhere in the code, and to the best of my knowledge, it's doing exactly what this describes.
clustering anomaly-detection outlier
asked 2 hours ago
ZayaZaya
101
New contributor
Zaya is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
What could cause the local outlier factor (LOF) to output below 1.0 for outliers and above 1.0 for inliers? I have my code sort of working just by inverting the output, but I can't figure out what's wrong with my algorithm. I'm following the one Wikipedia lists to the letter, but for some reason, it's producing the opposite result.
On a high, non-code-specific level, does anyone know what could cause the algorithm to behave like this? I've looked everywhere in the code, and to the best of my knowledge, it's doing exactly what this describes.
clustering anomaly-detection outlier
clustering anomaly-detection outlier
asked 2 hours ago
ZayaZaya
101
New contributor
Zaya is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 2 hours ago
ZayaZaya
101
New contributor
Zaya is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 2 hours ago
ZayaZaya
101
New contributor
Zaya is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 2 hours ago
ZayaZaya
101
asked 2 hours ago
ZayaZaya
101
101
New contributor
Zaya is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Zaya is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
Zaya is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
add a comment |
add a comment |
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