CompareMLAlgos_ML

The goal of this project is to compare the performance of different ML algorithms against different undersampled and oversampled datasets. Datasets used:

• Drug consumption
• Labor Relations
• Heart disease

Machine Learning Algorithms used

• Random Forest
• K-Neighbors
• Gradient Boosting
• MultiLayer Perceptron
• Support Vector Machine
• Decision Tree

The final accuracies have been recorded to perform friedman test.