Improving the expressiveness of black-box models for predicting student performance
暂无分享,去创建一个
Rafael Molina-Carmona | Faraón Llorens-Largo | Carlos Villagrá | Patricia Compañ-Rosique | Francisco José Gallego-Durán | Rosana Satorre-Cuerda | F. Llorens-Largo | R. Molina-Carmona | F. J. Gallego-Durán | Rosana Satorre-Cuerda | Patricia Compañ-Rosique | Carlos Villagrá
[1] Daniel Neagu,et al. Interpreting random forest models using a feature contribution method , 2013, 2013 IEEE 14th International Conference on Information Reuse & Integration (IRI).
[2] Rui Guo,et al. Participation-based student final performance prediction model through interpretable Genetic Programming: Integrating learning analytics, educational data mining and theory , 2015, Comput. Hum. Behav..
[3] Shane Dawson,et al. Mining LMS data to develop an "early warning system" for educators: A proof of concept , 2010, Comput. Educ..
[4] Vladimir N. Vapnik,et al. The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.
[5] Vladimir Vapnik,et al. Statistical learning theory , 1998 .
[6] Robert Tibshirani,et al. The Elements of Statistical Learning: Data Mining, Inference, and Prediction, 2nd Edition , 2001, Springer Series in Statistics.
[7] Shihong Huang,et al. Work in progress: A machine learning approach for assessment and prediction of teamwork effectiveness in software engineering education , 2012, 2012 Frontiers in Education Conference Proceedings.
[8] Peter R. Turner,et al. Predictive assessment of student performance for early strategic guidance , 2011, 2011 Frontiers in Education Conference (FIE).
[9] Rafael Molina-Carmona,et al. Boosting the Learning Process with Progressive Performance Prediction , 2015, EC-TEL.
[10] Chih-Jen Lin,et al. Probability Estimates for Multi-class Classification by Pairwise Coupling , 2003, J. Mach. Learn. Res..
[11] Chih-Jen Lin,et al. A Practical Guide to Support Vector Classication , 2008 .
[12] Sotiris B. Kotsiantis. Use of machine learning techniques for educational proposes: a decision support system for forecasting students’ grades , 2011, Artificial Intelligence Review.
[13] Rafael Molina-Carmona,et al. PREDICTING ACADEMIC PERFORMANCE FROM BEHAVIOURAL AND LEARNING DATA , 2016 .
[14] Chia-Lun Lo,et al. Developing early warning systems to predict students' online learning performance , 2014, Comput. Hum. Behav..
[15] Anna Szczepańska. Research Design and Statistical Analysis, Third Edition by Jerome L. Myers, Arnold D. Well, Robert F. Lorch, Jr , 2011 .
[16] Corinna Cortes,et al. Support-Vector Networks , 1995, Machine Learning.
[17] Ioanna Lykourentzou,et al. Early and dynamic student achievement prediction in e-learning courses using neural networks , 2009 .
[18] C. Villagrá Arnedo,et al. REAL-TIME EVALUATION , 2009 .
[19] Neil T. Heffernan,et al. Predicting College Enrollment from Student Interaction with an Intelligent Tutoring System in Middle School , 2013, EDM.
[20] Tobias Ley,et al. Which User Interactions Predict Levels of Expertise in Work-Integrated Learning? , 2013, EC-TEL.
[21] Jerome L. Myers,et al. Research Design and Statistical Analysis , 1991 .
[22] Shaobo Huang,et al. Predicting student academic performance in an engineering dynamics course: A comparison of four types of predictive mathematical models , 2013, Comput. Educ..
[23] Leland Wilkinson,et al. The History of the Cluster Heat Map , 2009 .
[24] Alex J. Bowers. Analyzing the Longitudinal K-12 Grading Histories of Entire Cohorts of Students: Grades, Data Driven Decision Making, Dropping out and Hierarchical Cluster Analysis. , 2010 .
[25] Ryan Shaun Joazeiro de Baker,et al. Educational Data Mining and Learning Analytics: Applications to Constructionist Research , 2014, Technology, Knowledge and Learning.
[26] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[27] Yoav Freund,et al. Experiments with a New Boosting Algorithm , 1996, ICML.
[28] Motoaki Kawanabe,et al. How to Explain Individual Classification Decisions , 2009, J. Mach. Learn. Res..
[29] Wilhelmiina Hämäläinen,et al. Comparison of Machine Learning Methods for Intelligent Tutoring Systems , 2006, Intelligent Tutoring Systems.
[30] Andreas Zell,et al. Interpreting linear support vector machine models with heat map molecule coloring , 2011, J. Cheminformatics.