Timeline for Semi-supervised learning: Classification vs Clustering
Current License: CC BY-SA 4.0
6 events
| when toggle format | what | by | license | comment | |
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| Feb 23, 2022 at 20:05 | answer | added | user318288 | timeline score: 1 | |
| Feb 23, 2022 at 19:02 | comment | added | J. Delaney | even if an algorithm is based on clustering the 'modified' part must include some elements of classification and vice verse, so I'm not convinced that you can so easily draw such a distinct line. How did you came with that conclusion anyway ? can you point to systematic studies that support it ? note that it only makes sense to compare performance when you test different algorithms on the exact same problem | |
| Feb 23, 2022 at 18:40 | comment | added | luke | These algorithms are all either based on a traditional classification algorithm or clustering algorithm though. Thats not blurry. i.e. s3vm -> classification, COP K Means -> clustering, EM multinomial Naive Bayes ->classification, etc. However virtually every classification based algo seems to outperform clustering. | |
| Feb 23, 2022 at 18:28 | comment | added | J. Delaney | As you say the distinction between semi-supervised classification and clustering is blurry, so your statement that one type of algorithms outperforms the other can't have clear meaning - it's a matter of which terminology is being used (the same algorithm can be called by both names) | |
| S Feb 23, 2022 at 17:51 | review | First questions | |||
| Feb 23, 2022 at 20:19 | |||||
| S Feb 23, 2022 at 17:51 | history | asked | luke | CC BY-SA 4.0 |