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Keyword: Synthetic Minority Oversampling Technique
Effects of Oversampling SMOTE in the Classification of Hypertensive Dataset
Hypertensive or high blood pressure is a medical condition that can be driven by several factors. These factors or variables are needed to build a classification model of the hypertension dataset. In the construction of classification models, class imbalance problems are often found due to oversampling. This research aims to obtain the best classification model…
Read More The Class Imbalance Problem in the Machine Learning Based Detection of Vandalism in Wikipedia across Languages
This paper analyses the impact of current trend in applying machine learning in detection of vandalism, with the specific aim of analyzing the impact of the class imbalance in Wikipedia articles. The class imbalance problem has the effect that almost all the examples are labelled as one class (legitimate editing); while far fewer examples are…
Read More Optimizing the Performance of Network Anomaly Detection Using Bidirectional Long Short-Term Memory (Bi-LSTM) and Over-sampling for Imbalance Network Traffic Data
Cybercriminal exploits integrity, confidentiality, and availability of information resources. Cyberattacks are typically invisible to the naked eye, even though they target a wide range of our digital assets, such as internet-connected smart devices, computers, and networking devices. Implementing network anomaly detection proves to be an effective method for identifying these malicious activities. The traditional anomaly…
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