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the project of Itai Schwed and Aviv Weinstein at the "supervised and unsupervised learning" course

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UnsupervisedProject

The dataset that we used contained samples with different wine properties:

http://archive.ics.uci.edu/ml/datasets/Wine+Quality

Our project is composed of two python files: 1- utils.py contains functions that we used in our project, for evaluating, plotting and more. 2- main.py contains a python script that does several things. First, the script will print in command line, the evaluations for all the algorithms. Additionally, it will automatically save all the graphs that we used in our work in a directory called "figures".

The dataset was also uploaded to our git directory in github under the directory "dataset".

In order to run our code, please run the following CMD: python main.py

After that, all the resulted should be returned as mentioned above.

Note: the code is based on many package constraints, so before running the code please make sure to create a CONDA environment, using the requirements.yml file.

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the project of Itai Schwed and Aviv Weinstein at the "supervised and unsupervised learning" course

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