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wxr99 / HolisticPU

Beyond Myopia: Learning from Positive and Unlabeled Data through Holistic Predictive Trends [NeurIPS 2023]
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About results on Credit Card dataset #4

Open Blue0rigin opened 6 months ago

Blue0rigin commented 6 months ago

Hi, thank you for your interesting work. I am interested in applying your method to a class-imbalanced problem similar to the credit card dataset in your paper. But when I run your "creditcard.py" code file, I can only get an AUC score of about 0.949, which is lower than the AUC score reported in Table 6 of the paper. Could you share more details (e.g., hyperparameter setting or other details that I may miss) on how to replicate the results in Table 6? Many thanks.

dean14367 commented 5 months ago

In analyzing the Credit Card dataset, several key findings emerged, shedding light on consumer behavior, risk factors, and financial trends. Through comprehensive data exploration and analysis, patterns regarding spending habits, payment behaviors, and creditworthiness were uncovered. These insights provide valuable guidance for financial institutions in refining their risk assessment strategies for what is vioc charge on credit card , tailoring product offerings, and enhancing customer experience.