Binary contingency table. حسب Lu Xiao (314030)

Feature Selection for Microarray Data Classification Using Hybrid Information Gain and a Modified Binary Krill Herd Algorithm حسب Ge Zhang (112487)

"…However, the high dimensionality of microarray datasets poses a serious challenge to most existing FS algorithms. …"

Optimizing Kernel Transformations to Handle Binary Class Imbalanced Dataset Classification حسب Vaibhavi Patel (19843282)

ROC curves of our out-of-class algorithm (blue) and a threshold decision boundary (red) representing the true positive rates (TPR) compared to the false positive rates (FPR) for te... حسب G. Christopher Marais (21492084)

Neyman-Pearson Multi-Class Classification via Cost-Sensitive Learning حسب Ye Tian (220278)

"…In this work, we tackle the multi-class NP problem by establishing a connection with the CS problem via strong duality and propose two algorithms. We extend the concept of NP oracle inequalities, crucial in binary classifications, to NP oracle properties in the multi-class context. …"

GSE96058 information. حسب Sepideh Zununi Vahed (9861298)

"…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …"

The performance of classifiers. حسب Sepideh Zununi Vahed (9861298)

"…Subsequently, feature selection was conducted using ANOVA and binary Particle Swarm Optimization (PSO). During the analysis phase, the discriminative power of the selected features was evaluated using machine learning classification algorithms. …"

Integrating terahertz time-domain spectroscopy with XGBoost for rapid and interpretable species-level wood identification of <i>Pterocarpus</i> حسب Min Yu (120607)

"…The results showed that the XGBoost model performed best, achieving 100% accuracy in binary classification (<i>P</i>. <i>santalinus</i> and <i>P</i>. …"

Data_Sheet_1_Identifying Depressed Essential Tremor Using Resting-State Voxel-Wise Global Brain Connectivity: A Multivariate Pattern Analysis.pdf حسب Yufen Li (428110)

"…</p><p>Methods: Based on global brain connectivity (GBC) mapping from 41 depressed ET, 49 non-depressed ET, 45 primary depression, and 43 healthy controls (HCs), multiclass Gaussian process classification (GPC) and binary support vector machine (SVM) algorithms were used to identify patients with depressed ET from non-depressed ET, primary depression, and HCs, and the accuracy and permutation tests were used to assess the classification performance.…"