<p>Of course. It only depends if those features are informative enough for the task at hand. In order to better understand the phenomenon, you can imagine 2 features displayed as points in a 2D plane. The number of possible target classes goes up to the number of clusters you can find in that plane.</p>

<p>About the suggestion, I can only recommend the utilisation of a non-linear classifier.</p>

CC BY-SA 4.0
2019-11-26T16:13:16.347Z
2019-11-26T16:13:16.347Z
David
<p>Is it possible to perform multiclass classification on data where the number of features is less than the number of target variables? Do you have any suggestions on how to address a problem where I have 2000 target variables?</p>

<machine-learning><classification>
Can I perform multiclass classification when the number of features is less than the number of targets?
ATidedHumour
# Can I perform multiclass classification when the number of features is less than the number of targets?

(Asked by: username_0 on 2019-11-26)

Is it possible to perform multiclass classification on data where the number of features is less than the number of target variables? Do you have any suggestions on how to address a problem where I have 2000 target variables?

**Tags:** machine-learning, classification


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## 1 answers

### Answer by username_1 on 2019-11-26. Score: 2 | Accepted answer

Of course. It only depends if those features are informative enough for the task at hand. In order to better understand the phenomenon, you can imagine 2 features displayed as points in a 2D plane. The number of possible target classes goes up to the number of clusters you can find in that plane.

About the suggestion, I can only recommend the utilisation of a non-linear classifier.


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