Problem 2: CART-RF-ANN Mortality Outcomes for Females Suffering Myocardial Infarction The mifem data frame has 1295 rows and 10 columns

Problem 2: CART-RF-ANN

Mortality Outcomes for Females Suffering Myocardial Infarction

The mifem data frame has 1295 rows and 10 columns. This is a Dataset of females having coronary heart disease (CHD). you have to predict with the given information whether the female is dead or alive so as to discover important factors that should be considered crucial in the treatment of the disease. Use CART, RF & ANN, and compare the models' performances in train and test sets.

1. 1. Data Ingestion: Read the dataset. Do the descriptive statistics and do null valuecondition check, write an inference on it.
   2. Encode the data (having string values) for Modelling. Data Split: Split the data into testand train, build classification model CART, Random Forest, Artificial Neural Network.
   3. Performance Metrics: Check the performance of Predictions on Train and Test sets usingAccuracy, Confusion Matrix, Plot ROC curve, and get ROC_AUC score for each model. 2.4 Final Model: Compare all the models and write an inference which model is best/optimized.

2.5 Inference: Basis on these predictions, what are the insights and recommendations?

Dataset for Problem 2: mifem.csv

Data Dictionary for mifem.csv :

1. Outcome: mortality outcome: a factor with levels live, dead
2. Age: age at onset
3. Yronset: year of onset (The year of onset is the year on which an individual acquires, develops, or first experiences a condition or symptoms of a disease or disorder)
4. Premi: previous myocardial infarction event, a factor with levels y, n, nk not known
5. Smstat: smoking status, a factor with levels c current, x ex-smoker, n non-smoker, nk not

known

6. Diabetes: a factor with levels y, n, nk not known
7. Highbp: high blood pressure, a factor with levels y, n, nk not known
8. Hichol: high cholesterol, a factor with levels y, n for yes and no
9. Angina: a factor with levels y, n, nk not known
10. Stroke: a factor with levels y, n, nk not known