Timeline for Outlier detection for a univariate categorical variable?
Current License: CC BY-SA 4.0
10 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Sep 8, 2020 at 12:03 | comment | added | Nick Cox | I don't agree at all that "for categorical variables there is no concept of outliers". What should be clear is that this hinges on what you define as an outlier and that procedures will necessarily differ from those for measured variables. | |
| Sep 8, 2020 at 12:00 | comment | added | Nick Cox | You're asking questions about a procedure I have never studied, let alone used. That seems to call for a completely new thread. | |
| Sep 8, 2020 at 10:45 | comment | added | Kapil | @NickCox: Also, can you clarify one more doubt regarding K-Mode Clustering. Like - 1) how we do feature engg. or dimensional reduction for categorical variables for ML model. 2) And how you evaluate your K-Model Clustering ML Model is giving good result (like- accuracy, etc). | |
| Sep 8, 2020 at 10:42 | comment | added | Kapil | Yes, for categorical variables there is no concept of outliers. | |
| Sep 3, 2020 at 10:42 | comment | added | Nick Cox | I don't understand what you are saying but I think you're agreeing with my comment. The mode is usually irrelevant in assessing outliers. | |
| Sep 3, 2020 at 10:17 | review | Late answers | |||
| Sep 3, 2020 at 10:20 | |||||
| Sep 3, 2020 at 10:13 | comment | added | Kapil | Yes, same way like if I had a below table having colors, based on frequency I can't say "Green' color is an outliers.It's applicable if the record counts in Millions as well. Red Red Red Black Black Black Green | |
| Sep 3, 2020 at 10:07 | comment | added | Nick Cox | No proof is needed or possible. This is not a topic for formal logic, just statistical judgment. But you need at least informally a definition of outlier. Here's one of mine for this context: An outlier is a unusual data value that causes surprise or needs some attention. If asked for gender, suppose 50 people say male, 49 people say female and 1 person says "none of your business". Then the last value could be regarded as an outlier in this sense only: you need to decide what to do about it. An outlier is not necessarily wrong or self-evidently to be ignored. | |
| Sep 3, 2020 at 10:05 | review | First posts | |||
| Sep 3, 2020 at 10:51 | |||||
| Sep 3, 2020 at 9:55 | history | answered | Kapil | CC BY-SA 4.0 |