Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In binary classification problems it is common for the two classes to be imbalanced: one case is very rare compared to the other.   consider the infinitely imbalanced case where one class has a finite sample size and the other class's sample size grows without bound. For logistic regression, the infinitely imbalanced case often has a useful solution. Under mild conditions, the intercept diverges as expected, but the rest of the coefficient vector approaches a non trivial and useful limit. That limit can be expressed in terms of exponential tilting and is the minimum of a convex objective function. The limiting form of logistic regression suggests a computational shortcut for fraud detection problems.
['Art B. Owen']
I am writing a research paper on a idea Infinitely Imbalanced Logistic Regression
[{"from": "human", "value": "I am writing a research paper on a idea Infinitely Imbalanced Logistic Regression"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: In binary classification problems it is common for the two classes to be imbalanced: one case is very rare compared to the other.   consider the infinitely imbalanced case where one class has a finite sample size and the other class's sample size grows without bound. For logistic regression, the infinitely imbalanced case often has a useful solution. Under mild conditions, the intercept diverges as expected, but the rest of the coefficient vector approaches a non trivial and useful limit. That limit can be expressed in terms of exponential tilting and is the minimum of a convex objective function. The limiting form of logistic regression suggests a computational shortcut for fraud detection problems."}]