Machine-Learning-Project

This is a final homework project for Introduction to Machine Learning (NPFL054) course in Charles University.

Files description

• task.pdf file contains the original description of the assignment which outlines what had to be done.
• code.R contains all the code that was used in order to obtain final results.
• report.pdf contains detailed analysis of the information obtained, including comparisson of those and final conclusion.

Techniques and approaches used

this is just an outline, for better analysis please refer to: report.pdf file

classification models used (wtih parameters in brackets that were tuned):

• Decision tree (complexity parameter)
• Random forest (number of trees, feature sample size)
• Regularized logistic regression (regularization parameter lambda, elasticity parameter alpha)