Timeline for How different classifiers would perform on a particular data set
Current License: CC BY-SA 4.0
4 events
| when toggle format | what | by | license | comment | |
|---|---|---|---|---|---|
| Oct 10, 2021 at 17:25 | comment | added | spectre | As stated above a decision tree might perform well as it can model in non linear relationships as well. Naive Bayes is usually used when we have a NLP task at hand as it can perform well on large dataset. KNN might or might not perform well. | |
| Oct 10, 2021 at 16:20 | comment | added | Parth Sharma | Decision tree will perform good however Naive bayes is a weak classifier due to many assumptions it holds as a result it will not perform well on such data set and same goes for KNN . A dataset forming above graph , KNN will not be able to perform well too. | |
| Oct 10, 2021 at 16:15 | comment | added | user9532692 | Thanks for your explanation. However, I am particularly interested in how decision tree, Naive Bayes, and KNN will perform on those datasets. | |
| Oct 10, 2021 at 15:54 | history | answered | Parth Sharma | CC BY-SA 4.0 |