svm_friction: A Python based software for calculating, data analysis and modeling the coefficient of friction of aluminum metal matrix composites using support vector regression

The Python software performs data analysis and modeling on the coefficient of friction (COF) of open-cell AlSi10Mg-SiC composites, which are tested by pin-on-disk method under dry sliding conditions. The software reads the experimental data from Excel files, calculates the average COF and time, saves the results to new files, prints and saves some descriptive statistics, merges the data into one DataFrame, and splits the data into training, validation, and testing sets for a support vector regression (SVR) model. The software also performs grid search to find the best hyperparameters for the SVR model, predicts the COF for the test and validation sets, calculates and saves some performance metrics, and plots and saves a histogram and a boxplot of the COF for the material. The software provides a simple, versatile, and extensible platform for other materials and models. The software is available at https://github.com/mihail-15/svm_friction.