Model v4
These was the steps of the model-v4 using Random Forest, I also used feature engineering and numerical and categorical transformations.
The model is 21_01_22_lr_w_v3.sav, and can be found on the respective directory.
Pipeline
graph TD
A[Transformed Data: second-eda-output.csv] --> B[Type conversion];
B[Type conversion] --> C[Train Test Split];
C[Train Test Split] --> D[One Hot Encoder on all categorical variables];
D[One Hot Encoder] --> E[Fit Random Forest];
E --> G[Predict];
G[Predict] --> H[Calculate Metrics];
classDef tune fill:#f96;
Confusion Matrix
Feature Importance
