Accuracy is not always the best metric to evaluate imbalanced data. ❎ ❎
- Especially in classification models like Loan Prediction. 💵 💵
- Accuracy basically is the number of correct predictions out of total predictions.🔍 🔎
- In these cases, Using accuracy here is like using a telescope to examine microorganisms.🔭.🔭
What do you think is the right parameter?❓❓
- Precision and Recall are better metrics to evaluate both classes in classification models. ✅ ✅
- Precision is of all the loans that we labeled as 'Bad', how many were actually 'Bad'? 🔬🔬
- Recall is of all the 'Bad Loans' that truly exist, how many did you correctly label as 'Bad'. 📏📏
🔥🔥Sometimes selection of accurate metrics to see how your model works perfectly is extremely important!💬 ✅
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#evaluationmetric #accuracy #precision #recall #confusionmatrix #mlshorts #datashorts #ExplainedIn60
