Salary Prediction with Analyzing Affected Elements by using Pearson Correlation
نویسندگان
چکیده
This paper proposes a model for predicting salaries based on the 1994 Census Database to predict whether final salary is over 50 thousand dollars or not. In order do this, researchers will identify various factors that may influence wages and analyze their impact salary. To find most accurate model, use 32561 records, each containing 15 elements, apply three different machine learning algorithms: Random Forest, Decision Trees, Logistic Regression. These algorithms be evaluated using 5-fold cross validation method, which commonly used technique measuring performance of models. The goal this study provide guidance wage levels individuals entering workforce, as well understand how affect an individual's information could useful job seekers, employers looking attract top talent. By identifying wages, also potentially help policy makers other stakeholders address issues inequality fairness in workforce. Overall, developed has potential valuable insights wide range organizations.
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ژورنال
عنوان ژورنال: BCP business & management
سال: 2023
ISSN: ['2692-6156']
DOI: https://doi.org/10.54691/bcpbm.v44i.4955