Table_1_Uncovering the Achilles heel of genetic heterogeneity: machine learning-based classification and immunological properties of necroptosis clusters in Alzheimer’s disease.XLS... حسب Huangwei Wei (17011266)

"…The Extreme Gradient Boosting (XGB) was found to be the most optimal diagnostic model for the AD based on the predictive ability and reliability of the models constructed by four machine learning approaches. …"

Image_2_Uncovering the Achilles heel of genetic heterogeneity: machine learning-based classification and immunological properties of necroptosis clusters in Alzheimer’s disease.TIF... حسب Huangwei Wei (17011266)

"…The Extreme Gradient Boosting (XGB) was found to be the most optimal diagnostic model for the AD based on the predictive ability and reliability of the models constructed by four machine learning approaches. …"

Image2_An evolution strategy of GAN for the generation of high impedance fault samples based on Reptile algorithm.TIF حسب Hao Bai (555291)

"…In this paper, we present an algorithm called Generative Adversarial Networks (GAN) based on the Reptile Algorithm (GANRA) for generating fault data and propose an evolution strategy based on GANRA to assist the fault detection of neural networks. …"

Image1_An evolution strategy of GAN for the generation of high impedance fault samples based on Reptile algorithm.TIF حسب Hao Bai (555291)

"…In this paper, we present an algorithm called Generative Adversarial Networks (GAN) based on the Reptile Algorithm (GANRA) for generating fault data and propose an evolution strategy based on GANRA to assist the fault detection of neural networks. …"

Image2_An evolution strategy of GAN for the generation of high impedance fault samples based on Reptile algorithm.TIF حسب Hao Bai (555291)

"…In this paper, we present an algorithm called Generative Adversarial Networks (GAN) based on the Reptile Algorithm (GANRA) for generating fault data and propose an evolution strategy based on GANRA to assist the fault detection of neural networks. …"

Image1_An evolution strategy of GAN for the generation of high impedance fault samples based on Reptile algorithm.TIF حسب Hao Bai (555291)

"…In this paper, we present an algorithm called Generative Adversarial Networks (GAN) based on the Reptile Algorithm (GANRA) for generating fault data and propose an evolution strategy based on GANRA to assist the fault detection of neural networks. …"

Data for "Machine Learning-based Prediction of Passive Gears from Vessel Tracking Data in Small-Scale Multi-gear Fisheries" حسب Pamela Lattanzi (16454871)

Algorithm comparison test results. حسب Hang Ren (1312905)

Run times of two algorithms. حسب Gourab Saha (8987405)

"…Multiple soil-parameter measuring sensors are used to identify suitable crop and fertilizer requirements for that land using IoT and machine learning. The ML model-based crop prediction showed 97.35% accuracy utilizing random forest algorithm. …"

The illustration depicts our CQ-CNN architecture for binary image classification. حسب Mominul Islam (3513758)

DataSheet1_Identification of a ferroptosis-related gene signature predicting recurrence in stage II/III colorectal cancer based on machine learning algorithms.DOCX حسب Ze Wang (132986)

"…We developed a machine learning framework with 83 combinations of 10 algorithms based on 10-fold cross-validation (CV) or bootstrap resampling algorithm to identify the most robust and stable model. …"

ESPDHot: An Effective Machine Learning-Based Approach for Predicting Protein–DNA Interaction Hotspots حسب Lianci Tao (16913613)

"…Combining the Boruta method with our previously developed Random Grouping strategy, we obtained an optimal set of features. Finally, a stacking classifier is constructed to output prediction results, which integrates three classical predictors, Support Vector Machine (SVM), XGBoost, and Artificial Neural Network (ANN) as the first layer, and Logistic Regression (LR) algorithm as the second one. …"

ESPDHot: An Effective Machine Learning-Based Approach for Predicting Protein–DNA Interaction Hotspots حسب Lianci Tao (16913613)

"…Combining the Boruta method with our previously developed Random Grouping strategy, we obtained an optimal set of features. Finally, a stacking classifier is constructed to output prediction results, which integrates three classical predictors, Support Vector Machine (SVM), XGBoost, and Artificial Neural Network (ANN) as the first layer, and Logistic Regression (LR) algorithm as the second one. …"

Although a Support Vector Machine (SVM) algorithm achieved the highest accuracy score of 99.89%, we utilized a Logistic Regression partition plot with two features to provide a gen... حسب Debashis Chatterjee (1790896)

Data_Sheet_1_oFVSD: a Python package of optimized forward variable selection decoder for high-dimensional neuroimaging data.pdf حسب Tung Dang (15229042)

"…Next, the hyperparameters of each ML model are optimized at each forward iteration. Final outputs highlight an optimized number of selected features (brain regions of interest) for each model with its accuracy. …"

Validation of image processing steps and metric results using images of a microfluidic device. حسب Gavrielle R. Untracht (11820311)

DataSheet1_A novel machine learning ensemble forecasting model based on mixed frequency technology and multi-objective optimization for carbon trading price.PDF حسب Zejun Li (176523)

"…Finally, the ensemble model based on deep learning strategy can effectively integrate the advantages of high-frequency and low-frequency data in complex datasets. …"

In Silico Prediction of Hemolytic Toxicity on the Human Erythrocytes for Small Molecules by Machine-Learning and Genetic Algorithm حسب Suqing Zheng (1585378)

"…To this end, we manually curate the hemolytic toxicity data set for the small molecules experimentally evaluated on the human erythrocytes, develop the first machine-learning (ML) based models to predict the human hemolytic toxicity of small molecules, harness the genetic algorithm (GA) and ML based model to optimize human hemolytic toxicity based on the molecular fingerprint to derive “optimal virtual fingerprints (OVFs)” with the desired hemolytic/nonhemolytic property, and finally implement a free software for the users to predict/optimize the human hemolytic toxicity with ML and GA in the automatic manner.…"

Related Work Summary. حسب Hend Bayoumi (22693738)

"…To enhance the offloading decision-making process, the algorithm incorporates the Newton-Raphson method for fast and efficient optimization of the computation rate under energy constraints. …"

Simulation parameters. حسب Hend Bayoumi (22693738)

"…To enhance the offloading decision-making process, the algorithm incorporates the Newton-Raphson method for fast and efficient optimization of the computation rate under energy constraints. …"