Timeline for How to make use of less data of a particular class for better modeling? [duplicate]
Current License: CC BY-SA 3.0
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| May 28, 2021 at 17:10 | comment | added | Marcel Braasch | You could look for samples with high entropy and give these more weight (active learning) | |
| May 28, 2021 at 16:54 | history | closed | kjetil b halvorsen♦ | Duplicate of When is unbalanced data really a problem in Machine Learning? | |
| May 28, 2021 at 16:52 | history | edited | kjetil b halvorsen♦ |
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| Apr 22, 2015 at 12:26 | comment | added | Sarath R Nair | @Jim K - Thanks to a new insight . It was really helpful. | |
| Apr 22, 2015 at 2:14 | history | edited | Nick Cox | CC BY-SA 3.0 |
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| Apr 22, 2015 at 2:12 | comment | added | Nick Cox | If either approach were a good idea, they would be explained prominently and early in every statistics course. But on the whole this is not a problem. The data are what they are. You might as well say that data with a few giants and a majority of people of more typical height is unbalanced, so we need to replicate the giants. Not so, even though very small frequencies can make quantities difficult to estimate. And sometimes very large groups are larger than we want to handle. But in your situation, on the whole, this problem is not a problem. | |
| Apr 22, 2015 at 2:08 | history | edited | Nick Cox | CC BY-SA 3.0 |
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| Apr 21, 2015 at 23:15 | comment | added | Jim K. | This answer to a similar question covers the details of how to implement a class weighting scheme in scikit-learn: stackoverflow.com/questions/18078084/… | |
| Apr 21, 2015 at 9:02 | review | First posts | |||
| Apr 21, 2015 at 9:43 | |||||
| Apr 21, 2015 at 8:58 | history | asked | Sarath R Nair | CC BY-SA 3.0 |