A comparison of LightGBM and perceptron for classifying the cause of salary differences between workgroups : Comparative study for classifying the reason for salary difference with different machine learning algorithms
Abstract: Machine learning is part of what is called AI. It is defined as the application of an algorithm to improve a result through learning. In Sweden, the law requires large companies and organizations to revise their salaries every year to ensure there is no wage disparity between men and women. This could be used as an assisting tool if machine learning is applied to the analysis process. By training two different models and test them against the same test dataset different metrics can be obtained and analyzed to see how they perform in comparison to each other. The results show a slightly improved performance by the perceptron and that there is room for further development. This study is limited to a smaller dataset for training and testing. But in the future, more relevant features and larger datasets could be added for training the models and lead to a more accurate model.
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