Download the dataset below containing 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. This data set is named $$Haberman$\text{'}$s Survival Data$$ because it was first used in Haberman, S$.$ J$.(1976).$ Generalized Residuals for Log$-$Linear Models, Proceedings of the $9$th International Biometrics Conference, Boston, pp$.104-122.$

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Final Exam Data Set

This data set has $306$ records. The following are the attributes.

Age of patient at time of operation $($numerical$)$

Patient's year of operation $($year $-1900,$ numerical$)$

Number of positive axillary nodes detected $($numerical$)$

Survival status $($class attribute$)$

$1=$ the patient survived $5$ years or longer

$2=$ the patient died within $5$ year

Please conduct a data mining project using this data set. The objective of the project is to find the best performing classification model to predict if a patient will survive $5$ years or longer after the surgery. Please follow the data mining methodology you learned in this course to conduct the project. In order to find the best performing model, you need to try all the appropriate algorithms that you have learned in this course and compare their performance. For each model, you need to take screenshots of the data mining process and the results. Interpret the results. Put all the screen shots and your answer in ONE word document. Export the data mining processes from RapidMiner into the process files. Submit the word document and the data mining processes.