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ashis2004
Is there an existing issue for this?
Feature Description
We have a model with an accuracy of 0.88, indicating that the model correctly predicts 88% of the resumes as suitable or unsuitable for a given job role. While this seems high, it's important to delve deeper into other metrics such as F1 score, precision, and recall to understand the model's true performance.
Accuracy of model is = 0.88 F1 of model is = 0.4 Precision of model is = 1.0 Recall of model is = 0.25
Use Case
this model include automated resume screening in large-scale recruitment processes, where the model can quickly eliminate unsuitable candidates with high confidence. It can also be used in niche hiring where precision is critical, such as in roles requiring specific certifications or experiences that are non-negotiable. Improving the recall, possibly by enhancing the feature set or utilizing more complex algorithms, would broaden the model's applicability and ensure a more comprehensive selection of suitable candidates.
Benefits
No response
Add ScreenShots
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Priority
High
Record