Early detection of network intrusions using a GAN-based one-class classifier
T Kim, W Pak - IEEE Access, 2022 - ieeexplore.ieee.org
Early detection of network intrusions is a very important factor in network security. However,
most studies of network intrusion detection systems utilize features for full sessions, making …
most studies of network intrusion detection systems utilize features for full sessions, making …
Towards Data-Centric AI: A Comprehensive Survey of Traditional, Reinforcement, and Generative Approaches for Tabular Data Transformation
Tabular data is one of the most widely used formats across industries, driving critical
applications in areas such as finance, healthcare, and marketing. In the era of data-centric …
applications in areas such as finance, healthcare, and marketing. In the era of data-centric …
[PDF][PDF] Analysis of software effort estimation by machine learning techniques
Software effort estimation is a crucial activity in software project management that involves
predicting the level of effort required to develop or maintain software applications. Accurate …
predicting the level of effort required to develop or maintain software applications. Accurate …
Multi-sensor Detection Design Via a Weighted Scheme with AUC and Information Theory
J Qian, J Zhang, A Zhang, Z Sun… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
In this article, a multisensor detection system is constructed for Herbal Medicine odor
detection and recognition based on a weighted scheme with area under curve (AUC) and …
detection and recognition based on a weighted scheme with area under curve (AUC) and …
An adaptive matrix-based evolutionary computation framework for EEG feature selection
Electroencephalogram (EEG) plays a significant role in emotion recognition because it
contains abundant information. However, due to the highly correlated EEG channels, a lot of …
contains abundant information. However, due to the highly correlated EEG channels, a lot of …
Hybrid Variable Selection Approach to Analyse High Dimensional Dataset
In light of the heterogeneous mode of collection and high dimensionality, most real-time
datasets collected may contain irrelevant, correlated, noisy, and missing variables. When …
datasets collected may contain irrelevant, correlated, noisy, and missing variables. When …
[PDF][PDF] Analysis of Software Effort Estimation by Machine Learning Techniques.
Software effort estimation is a crucial activity in software project management that involves
predicting the level of effort required to develop or maintain software applications. Accurate …
predicting the level of effort required to develop or maintain software applications. Accurate …
Analisa Splitting Criteria Pada Decision Tree dan Random Forest untuk Klasifikasi Evaluasi Kendaraan
A Nugroho - JSITIK: Jurnal Sistem Informasi dan …, 2022 - jurnal.ciptamediaharmoni.id
Klasifikasi adalah salah satu topik dalam data mining. Algoritma atau model yang termasuk
dalam klasifikasi antara lain Decision tree, K-NN, Naïve bayes. Decision tree merupakan …
dalam klasifikasi antara lain Decision tree, K-NN, Naïve bayes. Decision tree merupakan …
Diabetes Prediction Using Machine Learning Analytics: Ensemble Learning Techniques
Diabetes is an incurable disease which is due to a high level of sugar in the blood over a
long period of time. Hence, early prediction is required to reduce its severity significantly …
long period of time. Hence, early prediction is required to reduce its severity significantly …
Practical Considerations of Fully Homomorphic Encryption in Privacy-Preserving Machine Learning
Machine learning has been successfully applied to big data analytics across various
disciplines. However, as data is collected from diverse sectors, much of it is private and …
disciplines. However, as data is collected from diverse sectors, much of it is private and …