Salary Predictor System for Thailand Labour Workforce using Deep Learning
Autor: | Thongchai Kaewkiriya, Phuwadol Viroonluecha |
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Rok vydání: | 2018 |
Předmět: |
business.industry
Computer science Deep learning Feature extraction Feature selection 02 engineering and technology Machine learning computer.software_genre Field (computer science) Random forest Data modeling 030507 speech-language pathology & audiology 03 medical and health sciences Workforce 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence Salary 0305 other medical science business computer |
Zdroj: | 2018 18th International Symposium on Communications and Information Technologies (ISCIT). |
DOI: | 10.1109/iscit.2018.8587998 |
Popis: | The purpose of this research is to build the Salary Predictor System to predict monthly salary of employees in Thailand using the Deep Learning approach, which has rapidly increased distinguish attention in machine learning field. The dataset has gathered from well-known job search website which has more than 1.7 million users. Personal data from the first five months of 2018 is applied to the analysis and construct this model. We compared the performance with related algorithms such as Random Forest and Gradient Boost Trees. The feature selection methods were applied to Deep Learning after comparing. As a result of combining the feature selection with Deep Learning, the optimal result was 0.462 in R-squared and the rapid runtime is 15.37 seconds. |
Databáze: | OpenAIRE |
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