Classifying school scope using deep neural networks based on students` surrounding living environments

HIGHLIGHTS

• What: This research investigates school scope classification using Deep Neural Networks (DNN) focusing on students living environments and educational opportunities. By addressing the interplay of socioeconomic and educational factors the study aims to develop an analytical framework for understanding how environmental contexts shape academic trajectories. The research focuses on environmental factors like family background and social environment, providing a deeper, more complete understanding of how these variables influence school selection filling an important gap in existing literature. While previous research has used data mining techniques like Decision Trees (DT), RF, and SVM to predict student achievemen , the . . .
  

   

  

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