[HTML][HTML] A systematic review on artificial intelligence dialogue systems for enhancing English as foreign language students' interactional competence in the university
C Zhai, S Wibowo - Computers and Education: Artificial Intelligence, 2023 - Elsevier
Previous studies demonstrate that the use of artificial intelligence (AI) dialogue systems for
English as a Foreign Language (EFL) education has effectively improved university …
English as a Foreign Language (EFL) education has effectively improved university …
[HTML][HTML] Missing value imputation affects the performance of machine learning: A review and analysis of the literature (2010–2021)
Recently, numerous studies have been conducted on Missing Value Imputation (MVI),
intending the primary solution scheme for the datasets containing one or more missing …
intending the primary solution scheme for the datasets containing one or more missing …
缺失数据处理方法研究综述.
熊中敏， 郭怀宇， 吴月欣 - Journal of Computer Engineering …, 2021 - search.ebscohost.com
大数据时代, 数据爆炸式的增长, 数据获取变得更容易的同时数据缺失现象也更加普遍.
数据的缺失极大地降低了数据的实用性. 数据缺失问题的处理成为大数据处理的热点研究课题 …
数据的缺失极大地降低了数据的实用性. 数据缺失问题的处理成为大数据处理的热点研究课题 …
Classifier performance evaluation for lightweight IDS using fog computing in IoT security
In this article, a Host-Based Intrusion Detection System (HIDS) using a Modified Vector
Space Representation (MVSR) N-gram and Multilayer Perceptron (MLP) model for securing …
Space Representation (MVSR) N-gram and Multilayer Perceptron (MLP) model for securing …
An ensemble stacking algorithm to improve model accuracy in bankruptcy prediction
Bankruptcy analysis is needed to anticipate bankruptcy. Errors in predicting bankruptcy often
cause bankruptcy. Machine learning with high accuracy to analyze reversal must …
cause bankruptcy. Machine learning with high accuracy to analyze reversal must …
Bankruptcy prediction using fuzzy convolutional neural networks
SB Jabeur, V Serret - Research in International Business and Finance, 2023 - Elsevier
We propose a combined method for bankruptcy prediction based on fuzzy set qualitative
comparative analysis (fsQCA) and convolutional neural networks (CNN). Currently, CNNs …
comparative analysis (fsQCA) and convolutional neural networks (CNN). Currently, CNNs …
A new incomplete pattern belief classification method with multiple estimations based on KNN
The classification of missing data is a challenging task, because the lack of pattern attributes
may bring uncertainty to the classification results and most classification methods produce …
may bring uncertainty to the classification results and most classification methods produce …
Multiple imputation ensembles (MIE) for dealing with missing data
A Aleryani, W Wang, B De La Iglesia - SN Computer Science, 2020 - Springer
Missing data is a significant issue in many real-world datasets, yet there are no robust
methods for dealing with it appropriately. In this paper, we propose a robust approach to …
methods for dealing with it appropriately. In this paper, we propose a robust approach to …
Ischemic heart disease multiple imputation technique using machine learning algorithm
Medical data sets in profound data repository like the University of California Irvin (UCI) has
missing values. These essential data are used for multiple analyses by researchers in a …
missing values. These essential data are used for multiple analyses by researchers in a …
Missing Value Imputation Designs and Methods of Nature-Inspired Metaheuristic Techniques: A Systematic Review
Missing values are highly undesirable in real-world datasets. The missing values should be
estimated and treated during the preprocessing stage. With the expansion of nature-inspired …
estimated and treated during the preprocessing stage. With the expansion of nature-inspired …