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About Deep Learning With Data Transformation and Factor PDF
This document summarizes a research paper that proposes using deep learning techniques like LSTM and CNN to predict student performance. Specifically: - It analyzes data transformation techniques like quantile transforms and min-max scaling before inputting data into deep learning models. - The models are trained on over 4 million samples from a Vietnamese university to predict student performance based on past course results and other factors. - Experimental results show the proposed method provides good prediction accuracy, especially when using data transformation techniques. - A comparison is made between deep learning techniques and traditional machine learning for student performance prediction. - The results indicate the approach could be useful for practical applications in predicting student outcomes.
Detailed Information
| Author: | ['Juan Tarbes Vergara'] |
|---|---|
| Publication Year: | 2020 |
| Pages: | 12 |
| Language: | English |
| Format: | |
| Price: | FREE |
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