This paper proposes an ensemble forecasting model for carbon market volatility with
structural factors and non-structural Baidu search index. Firstly, wavelet analysis is …

With the rapid growth of online education, Knowledge tracing (KT) has become a well
established problem, which evaluates the knowledge states of students and predicts their …

Bayesian network classifiers remain of great interest in recent years, among which semi-
naive Bayesian classifiers which utilize superparent one-dependence estimators (SPODEs) …

Classification is one of the main problems of machine learning, and assessing the quality of
classification is one of the most topical tasks, all the more difficult as it depends on many …

In classification, a decision tree is a common model due to its simple structure and easy
understanding. Most of decision tree algorithms assume all instances in a dataset have the …

Averaged one-dependence estimators (AODE) is a state-of-the-art machine learning tool for
classification due to its simplicity, high computational efficiency, and excellent classification …

In artificial intelligence, an expert/intelligent systems can emulate the decision-making ability
of human experts. A good classification algorithm can provide significant assistance to …

Performance evaluation is significant in data classification. The existing evaluation methods
ignore the characteristics (such as classification difficulty) of each instance. In practice, it is …

In the field of intelligent risk control, an accurate and credible classification algorithm can
provide decision-making support to financial institutions. This study proposes an instance …

To accommodate multi-class scenarios, area under the receiver operating characteristic
(ROC) curve (AUC) has been extended to volume under the ROC hyper-surface (VUHS) to …