Under real-world conditions, faulty samples of key components (eg, bearings and cutting
tools, etc.) are typically limited and sparse. Additionally, their historical data is characterized …

The weak classifier ensemble algorithms based on the decision tree model, mainly include
bagging (eg, fandom forest-RF) and boosting (eg, gradient boosting decision tree, eXtreme …

The purpose of this research article was to contrast the benefits of the optimal probability
threshold adjustment technique with other imbalanced data processing techniques, in its …

Accurate identification and effective support of key blocks are crucial for ensuring the
stability and safety of rock slopes. The number of structural planes and rock blocks were …

Cholera is a leading cause of mortality in Nigeria. The two most significant predictors of
cholera are a lack of access to clean water and poor sanitary conditions. Other factors such …

In the field of data mining and machine learning, dealing with imbalanced datasets is one of
the most complex problems. The class imbalance issue significantly affects the classification …

Gearbox fault diagnosis is a crucial aspect of maintenance and reliability in automobile
engineering. In automobile vehicles, the gearbox is a vital component that facilitates efficient …

Edge machine learning brings intelligence to low-power devices at the periphery of a
network. By running machine learning algorithms on the Edge, classification can be …

Asymmetric data classification presents a significant challenge in machine learning (ML).
While ML algorithms are known for their ability to classify symmetric data effectively …

Big data analysis using machine learning has become challenging problem to solve today. It
become more challenging in classification problems when class distribution is imbalanced …