A survey of stealth malware attacks, mitigation measures, and steps toward autonomous open world solutions
As our professional, social, and financial existences become increasingly digitized and as
our government, healthcare, and military infrastructures rely more on computer technologies …
our government, healthcare, and military infrastructures rely more on computer technologies …
Data mining and education
KR Koedinger, S D'Mello… - Wiley …, 2015 - Wiley Online Library
An emerging field of educational data mining (EDM) is building on and contributing to a wide
variety of disciplines through analysis of data coming from various educational technologies …
variety of disciplines through analysis of data coming from various educational technologies …
Lightgbm: A highly efficient gradient boosting decision tree
Abstract Gradient Boosting Decision Tree (GBDT) is a popular machine learning algorithm,
and has quite a few effective implementations such as XGBoost and pGBRT. Although many …
and has quite a few effective implementations such as XGBoost and pGBRT. Although many …
A churn prediction model using random forest: analysis of machine learning techniques for churn prediction and factor identification in telecom sector
In the telecom sector, a huge volume of data is being generated on a daily basis due to a
vast client base. Decision makers and business analysts emphasized that attaining new …
vast client base. Decision makers and business analysts emphasized that attaining new …
Ernest: Efficient performance prediction for {Large-Scale} advanced analytics
Recent workload trends indicate rapid growth in the deployment of machine learning,
genomics and scientific workloads on cloud computing infrastructure. However, efficiently …
genomics and scientific workloads on cloud computing infrastructure. However, efficiently …
An empirical analysis of feature engineering for predictive modeling
J Heaton - SoutheastCon 2016, 2016 - ieeexplore.ieee.org
Machine learning models, such as neural networks, decision trees, random forests and
gradient boosting machines accept a feature vector and provide a prediction. These models …
gradient boosting machines accept a feature vector and provide a prediction. These models …
How deep is knowledge tracing?
M Khajah, RV Lindsey, MC Mozer - arXiv preprint arXiv:1604.02416, 2016 - arxiv.org
In theoretical cognitive science, there is a tension between highly structured models whose
parameters have a direct psychological interpretation and highly complex, general-purpose …
parameters have a direct psychological interpretation and highly complex, general-purpose …
A machine learning approach for tracking and predicting student performance in degree programs
J Xu, KH Moon… - IEEE Journal of Selected …, 2017 - ieeexplore.ieee.org
Accurately predicting students' future performance based on their ongoing academic records
is crucial for effectively carrying out necessary pedagogical interventions to ensure students' …
is crucial for effectively carrying out necessary pedagogical interventions to ensure students' …
[HTML][HTML] Optimizing ensemble weights and hyperparameters of machine learning models for regression problems
Aggregating multiple learners through an ensemble of models aim to make better
predictions by capturing the underlying distribution of the data more accurately. Different …
predictions by capturing the underlying distribution of the data more accurately. Different …
[HTML][HTML] Educational data mining techniques for student performance prediction: method review and comparison analysis
Y Zhang, Y Yun, R An, J Cui, H Dai… - Frontiers in psychology, 2021 - frontiersin.org
Student performance prediction (SPP) aims to evaluate the grade that a student will reach
before enrolling in a course or taking an exam. This prediction problem is a kernel task …
before enrolling in a course or taking an exam. This prediction problem is a kernel task …