I am a newbie in Machine Learning, I trained a binary classifier for bank loan prediction through Logistic Regression. I measured the accuracy of it with two methods: accuracy score and jaccard index. Accuracy score returns a value of 0.91 whereas jaccard score returns a value of 33. Why is jaccard sore showing such a low value.(Ik it is a really stupid question, but it would be really good if you could help me out)
The Jaccard index or score is often used for bounding boxes or semantic segmentation in machine learning, i.e. in computer vision problems. Your problem is a classification problem using tabular data, and therefore this metric is not really applicable for this type of problem. Accuracy (and maybe even more so precision and recall) are more valuable metrics to assess your model's accuracy.