Data Sheet 1_Explainable machine learning reveals ribosome biogenesis biomarkers in preeclampsia risk prediction.docx by 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 by Bernhard Vennemann (7434353)

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

Subjects:

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

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

Subjects: “…evolutionary genetic algorithm…”

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

Subjects: “…evolutionary genetic algorithm…”

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

Subjects:

Data_Sheet_1_Genetic Algorithms for Optimized Diagnosis of Alzheimer’s Disease and Frontotemporal Dementia Using Fluorodeoxyglucose Positron Emission Tomography Imaging.PDF by 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 by 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 by 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 by 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 by 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 by 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 by 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). …”

Concept of the Loss function in the case of Supervised Machine Learning and Physics Machine Learning approach. by Akshansh Mishra (21001499)

The structure of the proposed algorithm. by Mingbao Yang (14008799)

Classification performance of four machine learning algorithms on the test set. by Maryam Ahmadzadeh (8590380)

Key gene identification based on two machine learning algorithms. by Lijun Guo (605276)

Ranking machine learning algorithms based on AUC. by F. William Townes (3216846)

“…<p>Numeric values indicate the fraction of times the row algorithm has higher classification performance than the column algorithm. pglm: elastic net penalized logistic regression, svm: support vector machine with radial basis function, xgb: gradient boosted trees, nb: naive Bayes, knn: k-nearest neighbors.…”

Optimization algorithms performance comparison across benchmark functions. by Sundreen Asad Kamal (20390818)