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Towards fair, explainable and actionable clustering for learning analytics

, and . Proceedings of The 14th International Conference on Educational Data Mining (EDM21), page 847--851. (2021)

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Towards fair, explainable and actionable clustering for learning analytics., and . EDM, International Educational Data Mining Society, (2021)A Neighborhood Deep Neural Network Model using Sliding Window for Stock Price Prediction., , and . BigComp, page 69-74. IEEE, (2021)Taxi Demand Prediction using an LSTM-Based Deep Sequence Model and Points of Interest., , and . COMPSAC, page 1719-1724. IEEE, (2020)A survey on datasets for fairness‐aware machine learning, , , and . (Oct 1, 2021)A survey on datasets for fairness-aware machine learning, , , , and . WIREs Data Mining and Knowledge Discovery, (March 2022)A Review of Clustering Models in Educational Data Science Toward Fairness-Aware Learning, , and . (2023)A review of clustering models in educational data science towards fairness-aware learning., , and . CoRR, (2023)Data augmentation for dealing with low sampling rates in NILM, , , and . CoRR, (2021)Multi-fair Capacitated Students-Topics Grouping Problem., , and . PAKDD (1), volume 13935 of Lecture Notes in Computer Science, page 507-519. Springer, (2023)A Neighborhood-Augmented LSTM Model for Taxi-Passenger Demand Prediction., , , and . MASTER@PKDD/ECML, volume 11889 of Lecture Notes in Computer Science, page 100-116. Springer, (2019)