Mainak1792/Regression-and-SVMs

A look into the simple implementations of regression and SVMs

Regression-and-Classification

Regression

Dataset Link:

Aim:

Experiments: Look into report

Results:

Conclusion:

Classification

Dataset Link:

• Training Set :
• Test Set :

Aim:

• Classification using linear SVM: Plot the classification accuracy as a function of the parameter C.
• Classification using Gaussian (RBF) kernel SVM: Use K fold Cross-Validation and find the best accuracy and save the model. Use the trained SVM model to classify the test data set and write the results to a file using the same format as the training data set.

Experiments: Look into report

Results:

Classification using linear SVM

• Train Accuracy
• Test Accuracy

Classification using Gaussian (RBF) kernel SVM

• 

Conclusion: