Two-point crossover method. حسب Dhulfiqar Hakeem Dhayef (17729684)

الموضوعات:

Calculation results of commonly used machine learning algorithm models. حسب Qianhui He (13522729)

Reward function related parameters. حسب Honglei Pang (22693724)

الموضوعات:

Data Sheet 1_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.docx حسب Jingjing Chen (293564)

"…A multi-algorithm machine learning framework was employed to optimize predictive performance, with model interpretability achieved through SHapley Additive exPlanations and diagnostic accuracy validated by receiver operating characteristic curves. …"

Automated diagnosis of heart valve degradation using novelty detection algorithms and machine learning حسب Bernhard Vennemann (7434353)

The Effect of Machine Learning Algorithms on the Prediction of Layer-by-Layer Coating Properties حسب Tijana Šušteršič (14519970)

الموضوعات:

Results of proposed algorithms and algorithms in [9] for 18 instances. حسب Jin Zhang (53297)

Available functions in the phase-shifting package. حسب Raul Castañeda (13932971)

Available functions in the numerical propagation package. حسب Raul Castañeda (13932971)

Available functions in the phase reconstruction package. حسب Raul Castañeda (13932971)

The optimal solution set of NYN by using different algorithms. حسب Yi Tao (178829)

الموضوعات:

The optimal solution set of HN by using different algorithms. حسب Yi Tao (178829)

الموضوعات:

FAR-1: A Fast Integer Reduction Algorithm Compared to Collatz and Half-Collatz حسب Faizan Ali (21689861)

الموضوعات:

Data_Sheet_1_Genetic Algorithms for Optimized Diagnosis of Alzheimer’s Disease and Frontotemporal Dementia Using Fluorodeoxyglucose Positron Emission Tomography Imaging.PDF حسب Josefa Díaz-Álvarez (5572427)

"…Genetic algorithms, customized with K-Nearest Neighbor and BayesNet Naives as the fitness function, were developed and compared with Principal Component Analysis (PCA). …"

Table_4_Genetic Algorithms for Optimized Diagnosis of Alzheimer’s Disease and Frontotemporal Dementia Using Fluorodeoxyglucose Positron Emission Tomography Imaging.DOCX حسب Josefa Díaz-Álvarez (5572427)

"…Genetic algorithms, customized with K-Nearest Neighbor and BayesNet Naives as the fitness function, were developed and compared with Principal Component Analysis (PCA). …"

Table_1_Genetic Algorithms for Optimized Diagnosis of Alzheimer’s Disease and Frontotemporal Dementia Using Fluorodeoxyglucose Positron Emission Tomography Imaging.DOCX حسب Josefa Díaz-Álvarez (5572427)

"…Genetic algorithms, customized with K-Nearest Neighbor and BayesNet Naives as the fitness function, were developed and compared with Principal Component Analysis (PCA). …"

Table_2_Genetic Algorithms for Optimized Diagnosis of Alzheimer’s Disease and Frontotemporal Dementia Using Fluorodeoxyglucose Positron Emission Tomography Imaging.DOCX حسب Josefa Díaz-Álvarez (5572427)

"…Genetic algorithms, customized with K-Nearest Neighbor and BayesNet Naives as the fitness function, were developed and compared with Principal Component Analysis (PCA). …"

Table_5_Genetic Algorithms for Optimized Diagnosis of Alzheimer’s Disease and Frontotemporal Dementia Using Fluorodeoxyglucose Positron Emission Tomography Imaging.docx حسب Josefa Díaz-Álvarez (5572427)

"…Genetic algorithms, customized with K-Nearest Neighbor and BayesNet Naives as the fitness function, were developed and compared with Principal Component Analysis (PCA). …"

Data_Sheet_2_Genetic Algorithms for Optimized Diagnosis of Alzheimer’s Disease and Frontotemporal Dementia Using Fluorodeoxyglucose Positron Emission Tomography Imaging.PDF حسب Josefa Díaz-Álvarez (5572427)

"…Genetic algorithms, customized with K-Nearest Neighbor and BayesNet Naives as the fitness function, were developed and compared with Principal Component Analysis (PCA). …"

Table_3_Genetic Algorithms for Optimized Diagnosis of Alzheimer’s Disease and Frontotemporal Dementia Using Fluorodeoxyglucose Positron Emission Tomography Imaging.DOCX حسب Josefa Díaz-Álvarez (5572427)

"…Genetic algorithms, customized with K-Nearest Neighbor and BayesNet Naives as the fitness function, were developed and compared with Principal Component Analysis (PCA). …"