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Identifying At-Risk Students for Early Interventions - A Time-Series Clustering Approach.

, , , , , and . IEEE Trans. Emerg. Top. Comput., 5 (1): 45-55 (2017)

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Efficient Parallel Data Mining for Massive Datasets: Parallel Random Forests Classifier., , and . PDPTA, page 1142-1148. CSREA Press, (2005)Detecting Trojans Using Data Mining Techniques., , and . IMTIC, volume 20 of Communications in Computer and Information Science, page 400-411. Springer, (2008)Anti-matter detection: particle physics model for KDD Cup 2004., , and . SIGKDD Explor., 6 (2): 109-112 (2004)1-dimensional splines as building blocks for improving accuracy of risk outcomes models., and . KDD, page 841-846. ACM, (2004)A survey of data mining techniques for malware detection using file features., , and . ACM Southeast Regional Conference, page 509-510. ACM, (2008)Bootstrapping methodology for the Session-based Anomaly Notification Detector (SAND)., , and . ACM Southeast Regional Conference, page 175-179. ACM, (2006)Nonpooling Convolutional Neural Network Forecasting for Seasonal Time Series With Trends., , and . IEEE Trans. Neural Networks Learn. Syst., 31 (8): 2879-2888 (2020)Tree-structured model diagnostics for linear regression., , and . Mach. Learn., 74 (2): 111-131 (2009)The On-Line Survey System for Distance Learning Education at the University of Central Florida.. WebNet, AACE, (1998)Analytical Modeling of Data Mining Process Based on Distributed Tuple Space., , and . PDPTA, page 1135-1141. CSREA Press, (2005)