Exploring Temporal Data Splits in BaseModel ➡ bit.ly/3vcSASh @SAIRblog latest post spotlights @basemodelai data-splitting approach and how it connects with our vision of #BehavioralModeling. We recognize the importance of the temporal aspect that is shaping data in real-life settings, and we believe it should be reflected in model training and testing procedures. With BaseModel we make it not only feasible but also super easy thanks to our innovative approach to creating users' behavioral representations. With temporal splits, we are able to: 🔒 Prevent data leakage between train, validation, and test set. 📊 Provide more reliable results than standard testing methods. 🔄 Augment data by creating multiple training points from a single user history. #SAIR #SyneriseAIResearch #TemporalDataSplits