Details of 23 basic benchmark functions. حسب Ying Li (38224)

"…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …"

Related researches. حسب Ying Li (38224)

"…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …"

S1 Dataset - حسب Ying Li (38224)

"…In this paper, we present an improved mountain gazelle optimizer (IMGO) based on the newly proposed mountain gazelle optimizer (MGO) and design a binary version of IMGO (BIMGO) to solve the feature selection problem for medical data. …"

Table_1_An efficient decision support system for leukemia identification utilizing nature-inspired deep feature optimization.pdf حسب Muhammad Awais (263096)

"…To optimize feature selection, a customized binary Grey Wolf Algorithm is utilized, achieving an impressive 80% reduction in feature size while preserving key discriminative information. …"

Models and Dataset حسب M RN (9866504)

"…</p><p dir="ltr"><br></p><p dir="ltr"><b>RAO (Rao Optimization Algorithm):</b><br>RAO is a parameter-less optimization algorithm that updates solutions based on simple arithmetic operations involving the best and worst individuals in the population. …"

Summary of LITNET-2020 dataset. حسب Asmaa Ahmed Awad (16726315)

"…The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …"

SHAP analysis for LITNET-2020 dataset. حسب Asmaa Ahmed Awad (16726315)

"…The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …"

Comparison of intrusion detection systems. حسب Asmaa Ahmed Awad (16726315)

"…The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …"

Parameter setting for CBOA and PSO. حسب Asmaa Ahmed Awad (16726315)

"…The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …"

NSL-KDD dataset description. حسب Asmaa Ahmed Awad (16726315)

"…The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …"

The architecture of LSTM cell. حسب Asmaa Ahmed Awad (16726315)

"…The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …"

The architecture of ILSTM. حسب Asmaa Ahmed Awad (16726315)

"…The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …"

Parameter setting for LSTM. حسب Asmaa Ahmed Awad (16726315)

"…The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …"

LITNET-2020 data splitting approach. حسب Asmaa Ahmed Awad (16726315)

"…The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …"

Transformation of symbolic features in NSL-KDD. حسب Asmaa Ahmed Awad (16726315)

"…The ILSTM is based on the novel integration of the chaotic butterfly optimization algorithm (CBOA) and particle swarm optimization (PSO) to improve the accuracy of the LSTM algorithm. …"

Data_Sheet_1_A real-time driver fatigue identification method based on GA-GRNN.ZIP حسب Xiaoyuan Wang (492534)

"…In this paper, a non-invasive and low-cost method of fatigue driving state identification based on genetic algorithm optimization of generalized regression neural network model is proposed. …"

DataSheet_1_Multi-Parametric MRI-Based Radiomics Models for Predicting Molecular Subtype and Androgen Receptor Expression in Breast Cancer.docx حسب Yuhong Huang (115702)

"…We applied several feature selection strategies including the least absolute shrinkage and selection operator (LASSO), and recursive feature elimination (RFE), the maximum relevance minimum redundancy (mRMR), Boruta and Pearson correlation analysis, to select the most optimal features. We then built 120 diagnostic models using distinct classification algorithms and feature sets divided by MRI sequences and selection strategies to predict molecular subtype and AR expression of breast cancer in the testing dataset of leave-one-out cross-validation (LOOCV). …"

Table_1_iRNA5hmC: The First Predictor to Identify RNA 5-Hydroxymethylcytosine Modifications Using Machine Learning.docx حسب Yuan Liu (88411)

"…Afterward, we utilized a two-stage feature space optimization strategy to improve the feature representation ability, and trained a predictive model using support vector machine (SVM). …"

Supplementary Material 8 حسب Nishitha R Kumar (19750617)

"…</li><li><b>Adaboost: </b>A boosting algorithm that combines weak classifiers iteratively, refining predictions and improving the identification of antimicrobial resistance patterns.…"

An intelligent decision-making system for embryo transfer in reproductive technology: a machine learning-based approach حسب Sanaa Badr (20628838)

"…Binary classification models were developed to classify cases into two groups: those transferring two or fewer embryos and those transferring three or four. …"