Generating Life Course Trajectory Sequences with Recurrent Neural Networks and Application to Early Detection of Social Disadvantage

• Published in: Advanced Data Mining and Applications Vol. 10604; pp. 225 - 242
• Main Authors: Wu, Lin, Haynes, Michele, Smith, Andrew, Chen, Tong, Li, Xue
• Format: Book Chapter
• Language: English
• Published: Switzerland Springer International Publishing AG 2017; Springer International Publishing
• Series: Lecture Notes in Computer Science
• Subjects: Life course data trajectory; Mixture density model; Recurrent neural networks; Social disadvantage

Using long-running panel data from the Household, Income and Labour Dynamics in Australia (HILDA) survey collected annually between 2001 and 2015, we aim to generate a sequence of events for individuals by processing real life trajectories one step at a time and predict what comes next. This is moti...