This project is done as team project for CSC-722: Machine Learning Fundamentals class.
The project demonstrates the application of Support Vector Machines (SVM) to classify the species of iris flowers based on the popular Iris dataset. This dataset includes data on the sepal and petal measurements of 150 iris flowers from three different species: Setosa, Versicolor, and Virginica.
The project includes:
- Data Exploration and Preparation
- Grid search to find best parameters for SVM Classifier
- SVM implementation and comparision with different kernels
- K-fold Cross-Validation of the best SVM Classifier implementation