Library of the 55 different classification and regression machine-learning algorithms used by the ensemble predictor SuperLearner (SL.library) in the CBDA 2.0 implementation. by Simeone Marino (81051)

Binary contingency table. by Lu Xiao (314030)

An optimal solution for the HFS instance. by Xiang Tian (4369285)

Schematic diagram of the Dropout optimization. by Peng Yang (296696)

Dropout optimization model framework structure diagram. by Peng Yang (296696)

Comparison based on hard instances from [79]. by Xiang Tian (4369285)

Image 1_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.tif by Xuehui Fan (10762662)

Data Sheet 7_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

Data Sheet 2_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

Data Sheet 9_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.xlsx by Xuehui Fan (10762662)

Data Sheet 5_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

Data Sheet 8_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

Data Sheet 6_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

Data Sheet 1_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

Data Sheet 3_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

Data Sheet 4_Prediction of outpatient rehabilitation patient preferences and optimization of graded diagnosis and treatment based on XGBoost machine learning algorithm.docx by Xuehui Fan (10762662)

Python-Based Algorithm for Estimating NRTL Model Parameters with UNIFAC Model Simulation Results by Se-Hee Jo (20554623)

“…The algorithm was applied to aqueous, binary mixture systems composed of 37 common biochemical substances such as amino acids, organic acids, and sugars. …”

Improved support vector machine classification algorithm based on adaptive feature weight updating in the Hadoop cluster environment by Jianfang Cao (1881379)

Face recognition accuracy of distinctive ways. by Yan Liu (25061)

Changes in loss curves of different models. by Yan Liu (25061)