Randomized Optimization (CS7641) 1. Download/clone the code from the repository - https://github.com/deepika-sivakumar/cs7641-randomized-optimization.git 2. Datasets from UCI machine learning repository: White wine quality dataset - https://archive.ics.uci.edu/ml/datasets/Wine+Quality Datasets can also be accessed from the folder. 3. Python version used - python 3.8 4. Packages to install mlrose_hiive pandas numpy sklearn datetime matplotlib 5. Run the following python files to generate graphs, one_max.py conti_peaks.py knapsack.py NN_tuning.py RO_comparison.py 6. util.py consists of the helper functions to generate the graphs 7. The generated graphs can be found inside the folder "graphs", within subfolders om,cp,ks for the corresponding algorithms.