Project Objective:

To predict whether a patient will survive 5 years or more after the operation based on age, year of operation and the number of positive axillary nodes.

Dataset description:

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.

Dataset: https://archive.ics.uci.edu/ml/datasets/haberman's+survival

Attribute Information:

1. Age of patient at time of operation (numerical)
2. Patient's year of operation (year - 1900, numerical)
3. Number of positive axillary nodes detected (numerical)
4. Survival status (class attribute) -- 1 = the patient survived 5 years or longer , 2 = the patient died within 5 year

Conclusion:

1. Patient’s age and year of operation alone are not deciding factors for the patient's survival.
2. Patients with less number of positive axillary nodes may have higher chances of survival although this may not be true in all cases.
3. People less than 35 years may have more chance of survival.
4. The objective of classifying the survival status of a new patient based on the given features is a difficult task.

You can also check out the code on Kaggle :

https://www.kaggle.com/kartikmohan1999/eda-on-haberman-dataset