S and V shaped transfer functions. by Chenyi Zhu (9383370)

“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”

S- and V-Type transfer function diagrams. by Chenyi Zhu (9383370)

“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”

Collaborative hunting behavior. by Chenyi Zhu (9383370)

“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”

Friedman average rank sum test results. by Chenyi Zhu (9383370)

“…To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”

Random forest model performs better than support vector machine algorithms and when it primarily uses spontaneous photopic ERG of 60-s duration in humans. by Ramsés Noguez Imm (6658637)

RMSE on the test data when fitting (logistic) quadratic models to binary data across increasing measurement error values . by Jakub Stoklosa (3315042)

Top-performing model configuration and performance by algorithm type. by Uğur Ejder (22683228)

Subjects:

Surround Suppression mechanism. by Elnaz Nemati (21402730)

Confusion matrix for a binary outcome (adapted from Fawcett [30]). by João Albuquerque (12936572)

Generalized Tensor Decomposition With Features on Multiple Modes by Jiaxin Hu (1327875)

“…An efficient alternating optimization algorithm with provable spectral initialization is further developed. …”

Effects of Class Imbalance and Data Scarcity on the Performance of Binary Classification Machine Learning Models Developed Based on ToxCast/Tox21 Assay Data by Changhun Kim (682542)

“…In this study, the effects of CI and data scarcity (DS) on the performance of binary classification models were investigated using ToxCast bioassay data. …”

The comparison of the accuracy score of the benchmark and the proposed models. by Uğur Ejder (22683228)

Subjects:

The prediction accuracy of simple versus hybrid models. by Uğur Ejder (22683228)

Subjects:

Convergence curve of feature selection algorithms across 11 datasets with KNN classifier. by Yi Wei Tye (22208735)

Flow diagram of the proposed model. by Uğur Ejder (22683228)

Subjects:

Solubility Prediction of Different Forms of Pharmaceuticals in Single and Mixed Solvents Using Symmetric Electrolyte Nonrandom Two-Liquid Segment Activity Coefficient Model by Getachew S. Molla (6416744)

“…., nonelectrolyte, electrolyte, and solvate) in single and mixed solvents using a symmetrically reformulated electrolyte nonrandom two-liquid segment activity coefficient (eNRTL-SAC) model. The methodology incorporates key features of the symmetric eNRTL-SAC model structure to reduce the number of parameters and uses a hybrid of global search algorithms for parameter estimation. …”

Comparison of baseline and hybrid machine learning models in predicting IVF outcomes (%). by Uğur Ejder (22683228)

Subjects:

Application of ABC SMC to the fitting of the binary flip with cusp model. by Elena Camacho-Aguilar (10906327)

The accuracy score change matrix following model development. by Uğur Ejder (22683228)

Subjects:

The statistical description of the original data set of the patients (<i>n</i> = 162). by Uğur Ejder (22683228)

Subjects: