<p>You have a situation where class imbalance is quite high. There are two ways to tackle this:</p>
<ol>
<li>Use Focal loss which focuses on underrepresented classes.</li>
<li>Train a Siamese network and allied techniques to it.</li>
</ol>

CC BY-SA 4.0
2022-09-19T20:22:27.443Z
2022-09-19T20:22:27.443Z
Abhishek Verma
<p>I'm training a model where the samples success rate is low.</p>
<p>I mean how do I tackle such situation - maybe only show the samples which match but then the ones that doesn't may match too.</p>
<p>But on the other hand if I train it with all the samples it seems like it never fully matches when it should.</p>
<p>Any ideas?</p>

CC BY-SA 4.0
2022-09-18T13:48:20.507Z
I think you need to specify your question: What do you mean by 'samples success rate', 'samples that match' and what is 'it' referring to in 'seems like it never fully matches when it should'?.
Chillston
CC BY-SA 4.0
2022-09-18T17:52:24.683Z
Please clarify your specific problem or provide additional details to highlight exactly what you need. As it's currently written, it's hard to tell exactly what you're asking.
Community
CC BY-SA 4.0
2022-09-18T19:54:12.880Z
Are you referring to something related to class imbalance?
Dave
<training>
How do you train a model with low success rate?
AnArrayOfFunctions
# How do you train a model with low success rate?

(Asked by: username_0 on 2022-09-18)

I'm training a model where the samples success rate is low.

I mean how do I tackle such situation - maybe only show the samples which match but then the ones that doesn't may match too.

But on the other hand if I train it with all the samples it seems like it never fully matches when it should.

Any ideas?

**Tags:** training

> **Comments:**
> **username_1**: I think you need to specify your question: What do you mean by 'samples success rate', 'samples that match' and what is 'it' referring to in 'seems like it never fully matches when it should'?.  
> **username_2**: Please clarify your specific problem or provide additional details to highlight exactly what you need. As it's currently written, it's hard to tell exactly what you're asking.  
> **username_3**: Are you referring to something related to class imbalance?  

---

## 1 answers

### Answer by username_4 on 2022-09-19. Score: 1

You have a situation where class imbalance is quite high. There are two ways to tackle this:

1. Use Focal loss which focuses on underrepresented classes.
2. Train a Siamese network and allied techniques to it.


---

