Data Visualization with Haberman Dataset

Haberman, S. J. (1976). Generalized Residuals for Log-Linear Models, Proceedings of the 9th International Biometrics Conference, Boston, pp. 104-122. Landwehr, J. M., Pregibon, D., and Shoemaker, A. C. (1984), Graphical Models for Assessing Logistic Regression Models (with discussion), Journal of the American Statistical Association 79: 61-83. Lo, W.-D. (1993). Logistic Regression Trees, PhD thesis, Department of Statistics, University of Wisconsin, Madison, WI. Relevant Information: The dataset contains cases from a study that was conducted between 1958 and 1970 at the University of Chicago’s Billings Hospital on the survival of patients who had undergone surgery for breast cancer.

Problem Statement : To predict whether a patient will survive after 5 years or not based upon the patient’s medical hisotry.

Source : https://www.kaggle.com/gilsousa/habermans-survival-data-set

Real-world/Business Objectives and Constraints :

1. The cost of a mis-classification can be very high.
2. No strict latency concerns.

To learn more please visit : Here