Project 1

Apply all five different machine learning models Logistic Regression, K-Nearest Neighbours Classifier, Support Vector machine, Decision Tree Classifier, Random Forest Classifier on
the given dataset.

Ans.

Based on the provided model accuracies, here are some conclusions:

1. K-Nearest Neighbors (KNN):

   • Highest Accuracy: 90.16%
   • KNN seems to be the most accurate model among those tested.

2. Support Vector Machine (SVM):

   • Accuracy: 86.89%
   • SVM performs well, showing robustness in classification.

3. Logistic Regression:

   • Accuracy: 85.25%
   • Logistic Regression also provides a good level of accuracy, making it a reliable model.

4. Random Forest:

   • Accuracy: 85.25%
   • Random Forest demonstrates competitive performance with other models.

5. Decision Tree:

   • Accuracy: 80.33%
   • Decision Tree, while still effective, has slightly lower accuracy compared to other models.