This is one of the project assigned to me by Computation Intelligence course.

I was asked to use Perceptron, SVM and new Perceptron (uses kernel) models with specific Flight dataset. I used sklearn models for this purpose and analized the result in detail with visual charts and diagram.

• Features
• Contributors
• License

For each model I tested each Hyperparameters to obtain the best value for them in order to increase the overal accuracy.

Used models:

• Perceptron
• GridSearchCV
• RepeatedStratifiedKFold
• SVC (with 4 different kernel)
• LinearSVC
• KerneledPerceptron

In order to maximize the accuracy of Perceptron model for non-linear datasets I reimplemeted KerneledPerceptron to use kernels like gussian, polynomial and linear.

Feel free to share your ideas or any other problems. Pull requests are welcomed.

SVM-Perceptron is released under an MIT license. See LICENSE for more information.