akashnigam69/heart_attack_analysis_and_prediction

Heart_attack_analysis_and_prediction

1.Within the scope of the project, we first made the data set ready for Exploratory Data Analysis(EDA)

2.We performed Exploratory Data Analysis(EDA).

3.We analyzed numerical and categorical variables within the scope of univariate analysis by using Distplot and Pie Chart graphics.

4.Within the scope of bivariate analysis, we analyzed the variables among each other using FacetGrid, Count Plot, Pair Plot, Swarm plot, Box plot, and Heatmap graphics.

5.We made the data set ready for the model. In this context, we struggled with missing and outlier values.

6.We used four different algorithms in the model phase.

7.We got 87% accuracy and 88% AUC with the Logistic Regression model.

8.We got 83% accuracy and 85% AUC with the Decision Tree Model.

9.We got 83% accuracy and 89% AUC with the Support Vector Classifier Model.And we got 90.3% accuracy and 93% AUC with the Random Forest Classifier Model.

10.When all these model outputs are evaluated, we prefer the model we created with the Random Forest Algorithm, which gives the best results.