HEART FAILURE UNSUPERVISED LEARNING

Importation made

the model used in this research is Logistic Regression and Decision Tree

Data understanding was made like trying to find the shape ,checking the datatypes and checking for null values and finding the short description of the dataset like the mean ,median ,std,25%,50%,75% and the max

Do feature Engineering by removing the categorical dataset

Then the correlation, finding how the factors are correlated

Finding the distribution of heart disease to age

Finding the distribution of chest pain with respect to male and female

Box plot is good for checking outliers
it helps getting  minimum , first quartile ,Median , third Quartile, Maximum        

Making prediction and checking for heart failure

The code is in my Github https://github.com/Keganwealths/Heartfailure_unsupervised_learning/tree/master