Data Mining in Python

This repository contains 3 experiments. Each experiment focuses on one type of mining problem. The first experiment focuses on association rules, the second on classification and the third on cluster analysis. The aim is to compare how available Python libraries for data mining are coping with each type of data mining problem. The libraries that were used: scikit-learn, mlxtend, PyCaret.

The experiments were implemented using Jupyter Notebook and must run in Python in version 3.8.0.

The packages needed to run the experiment are notebook, scikit-learn, mlxtend, pycaret, which are installed using the pip3 install <package_name> command. The other packages will be installed additionally as dependencies.

Content of the repository

experiments - a directory containing jupyter notebooks with all the source code:

1. association-rules-experiment.ipynb
2. classification-experiment.ipynb
3. cluster-analysis-experiment.ipynb

datasets - directory containing all source data for experiments

README.md - documentation