I am trying to understand which model might work for a given problem before trying the models, I find this case against my knowledge. Please guide what I am missing. I am new to Data Science.
Now you can see the boundaries are very much overlapping. The theory for SVM says that this model might work best with overlapping non linear data, which does not seems to be this case.
But still its able to identify all data in test set. So can you provide some clarity on why SVM performing good in this.
So my final results it is below order:
- Logistic Regression and SVM are same (Accuracy Score : 1.0)
- Random Forest (Accuracy Score : 0.9680851063829787)
- KNN (Accuracy Score : 0.925531914893617)
other details :
- feature set : 40
- sample data : around 500