This project depicts the code part of my seminar thesis about feature selection in regression tasks, where i dive deeper into the functionality of subset selection and regularization methods. The functionality lies in underlying_functions.py, while the illustrations are shown in Jupyter_Overview.ipynb. The Analysis is made using an NBA 🏀 data set, deployed here, this data set contains the playing and salary data for NBA players of the 2021/22 season. The goal of the Analysis was to detect the in game statistics, that have the best prediction power in a linear regression setting, where our target variable is the salary of a player.
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feature selection in regression tasks (application on NBA data)
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