Educational data mining to predict students' academic performance: A survey study
Educational data mining is an emerging interdisciplinary research area involving both
education and informatics. It has become an imperative research area due to many …
education and informatics. It has become an imperative research area due to many …
Incremental learning from unbalanced data with concept class, concept drift and missing features: a review
P Kulkarni, R Ade - International Journal of Data Mining & …, 2014 - search.proquest.com
Recently, stream data mining applications has drawn vital attention from several research
communities. Stream data is continuous form of data which is distinguished by its online …
communities. Stream data is continuous form of data which is distinguished by its online …
Comparative Study on Marks Prediction using Data Mining and Classification Algorithms.
B Kapur, N Ahluwalia… - International Journal of …, 2017 - search.ebscohost.com
Today that collecting data has been easy more than ever in almost all aspects of life, but the
collected data is of no use if it can't be efficiently utilised for the betterment of the society …
collected data is of no use if it can't be efficiently utilised for the betterment of the society …
Case-base maintenance of a personalised and adaptive CBR bolus insulin recommender system for type 1 diabetes
People with type 1 diabetes must control their blood glucose level through insulin infusion
either with several daily injections or with an insulin pump. However, estimating the required …
either with several daily injections or with an insulin pump. However, estimating the required …
Logistic regression learning model for handling concept drift with unbalanced data in credit card fraud detection system
P Kulkarni, R Ade - Proceedings of the Second International Conference …, 2016 - Springer
Credit card is the well-accepted manner of remission in financial field. With the rising
number of users across the globe, risks on usage of credit card have also been increased …
number of users across the globe, risks on usage of credit card have also been increased …
Evaluating machine learning techniques for improved adaptive pedagogy
M Dlamini, WS Leung - 2018 IST-Africa Week Conference (IST …, 2018 - ieeexplore.ieee.org
Literature has shown that learning gains may be improved significantly if students are
offered individual attention. The traditional offering of such individualised attention is …
offered individual attention. The traditional offering of such individualised attention is …
Prediction for student academic performance using SMNaive Bayes model
B Jia, K Niu, X Hou, N Li, X Peng, P Gu… - Advanced Data Mining and …, 2019 - Springer
Predicting students academic performance is very important for students future
development. There are a large number of students who can not graduate from colleges on …
development. There are a large number of students who can not graduate from colleges on …
[引用][C] A comparative analysis on the evaluation of classification algorithms in the prediction of students performance
C Anuradha, T Velmurugan - Indian Journal of Science and technology, 2015
Exploring approaches to educational data mining and learning analytics, to measure the level of acquisition of student's learning outcome
DB Fernández, S Lujan-Mora - EDULEARN16 Proceedings, 2016 - library.iated.org
The Educational Data Mining community website defines educational data mining
as:“Educational Data Mining is an emerging discipline, concerned with developing methods …
as:“Educational Data Mining is an emerging discipline, concerned with developing methods …
[PDF][PDF] Towards an Online Incremental Approach to Predict Students Performance.
C Labba, A Boyer - CSEDU (2), 2024 - members.loria.fr
Analytical models developed in offline settings with pre-prepared data are typically used to
predict students' performance. However, when data are available over time, this learning …
predict students' performance. However, when data are available over time, this learning …