[HTML][HTML] A review of ensemble learning and data augmentation models for class imbalanced problems: combination, implementation and evaluation
Class imbalance (CI) in classification problems arises when the number of observations
belonging to one class is lower than the other. Ensemble learning combines multiple models …
belonging to one class is lower than the other. Ensemble learning combines multiple models …
Past, present, and future of EEG-based BCI applications
An electroencephalography (EEG)-based brain–computer interface (BCI) is a system that
provides a pathway between the brain and external devices by interpreting EEG. EEG …
provides a pathway between the brain and external devices by interpreting EEG. EEG …
Prediction of rapid chloride penetration resistance of metakaolin based high strength concrete using light GBM and XGBoost models by incorporating SHAP analysis
This study investigates the non-linear capabilities of two machine learning prediction
models, namely Light GBM and XGBoost, for predicting the values of Rapid Chloride …
models, namely Light GBM and XGBoost, for predicting the values of Rapid Chloride …
Predicting hard rock pillar stability using GBDT, XGBoost, and LightGBM algorithms
Predicting pillar stability is a vital task in hard rock mines as pillar instability can cause large-
scale collapse hazards. However, it is challenging because the pillar stability is affected by …
scale collapse hazards. However, it is challenging because the pillar stability is affected by …
EEG-based emotion recognition using 4D convolutional recurrent neural network
In this paper, we present a novel method, called four-dimensional convolutional recurrent
neural network, which integrating frequency, spatial and temporal information of …
neural network, which integrating frequency, spatial and temporal information of …
A comparative performance of machine learning algorithm to predict electric vehicles energy consumption: A path towards sustainability
The rapid growth of transportation sector and related emissions are attracting the attention of
policymakers to ensure environmental sustainability. Therefore, the deriving factors of …
policymakers to ensure environmental sustainability. Therefore, the deriving factors of …
Application of artificial intelligence techniques for brain-computer interface in mental fatigue detection: a systematic review (2011-2022)
Mental fatigue is a psychophysical condition with a significant adverse effect on daily life,
compromising both physical and mental wellness. We are experiencing challenges in this …
compromising both physical and mental wellness. We are experiencing challenges in this …
A novel scheme for map** of MVT-type Pb–Zn prospectivity: LightGBM, a highly efficient gradient boosting decision tree machine learning algorithm
The gradient boosting decision tree is a well-known machine learning algorithm. Despite
numerous advancements in its application, its efficiency still needs to be improved for large …
numerous advancements in its application, its efficiency still needs to be improved for large …
A model combining multi branch spectral-temporal CNN, Efficient Channel attention, and LightGBM for MI-BCI classification
Accurately decoding motor imagery (MI) brain-computer interface (BCI) tasks has remained
a challenge for both neuroscience research and clinical diagnosis. Unfortunately, less …
a challenge for both neuroscience research and clinical diagnosis. Unfortunately, less …
E-CatBoost: An efficient machine learning framework for predicting ICU mortality using the eICU Collaborative Research Database
Improving the Intensive Care Unit (ICU) management network and building cost-effective
and well-managed healthcare systems are high priorities for healthcare units. Creating …
and well-managed healthcare systems are high priorities for healthcare units. Creating …