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