over-under sampling in Imbalance dataset and ROC in python

Dear sir I am a python developer with 8 years of professional experience. I have rich experiences of machine learning and data management. Especially I am familiar with oversampeling, undersampling of data and logistic regression. I am interested in this job and am ready to start the work. Looking forward to hearing from you soon. Best Regards, Yongtao J

Experienced data scientist have worked with imbalanced datasets and used under sampling, oversampling to achieve best possible results (preventing classifier from classifying all points with dominant label). Would like to see a sample dataset. Looking forward to hearing back from you.

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I am machine learning engineer and a data analyst I have been using numpy and sklearn and pandas and sklean for 3 years now

Package imblanced-learn provides many sampling methods to balance the imbalanced dataset. I have just work for a project to predict node failure. It is imbalanced, too. I am experienced, I can help.

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I have worked with imbalanced datasets in several occasions in the past. I can use the dataset and create the balanced dataset using over sampling or under-sampling. Then I can use Logistic Regression and use different metrics like ROC and F1 to evaluate. I can easily do this job without much hassle.