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

“…This algorithm conducts a series of procedures: (1) fragmentation of the molecules into functional groups from SMILES, (2) calculation of activity coefficients under predetermined temperature and mole fraction conditions by employing universal quasi-chemical functional group activity coefficient (UNIFAC) model, and (3) regression of NRTL model parameters by employing UNIFAC model simulation results in the differential evolution algorithm (DEA) and Nelder–Mead method (NMM). …”

Pair Potentials as Machine Learning Features by Jun Pei (1765720)

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Pair Potentials as Machine Learning Features by Jun Pei (1765720)

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Pair Potentials as Machine Learning Features by Jun Pei (1765720)

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PyNoetic’s classification module supports a range of popular and widely used ML classification models with just a single line of function call. by Gursimran Singh (575288)

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Table2_Prognostic Value of mRNAsi/Corrected mRNAsi Calculated by the One-Class Logistic Regression Machine-Learning Algorithm in Glioblastoma Within Multiple Datasets.DOCX by Mingwei Zhang (661218)

Table4_Prognostic Value of mRNAsi/Corrected mRNAsi Calculated by the One-Class Logistic Regression Machine-Learning Algorithm in Glioblastoma Within Multiple Datasets.DOCX by Mingwei Zhang (661218)

Table1_Prognostic Value of mRNAsi/Corrected mRNAsi Calculated by the One-Class Logistic Regression Machine-Learning Algorithm in Glioblastoma Within Multiple Datasets.DOCX by Mingwei Zhang (661218)

Table5_Prognostic Value of mRNAsi/Corrected mRNAsi Calculated by the One-Class Logistic Regression Machine-Learning Algorithm in Glioblastoma Within Multiple Datasets.DOCX by Mingwei Zhang (661218)

Table3_Prognostic Value of mRNAsi/Corrected mRNAsi Calculated by the One-Class Logistic Regression Machine-Learning Algorithm in Glioblastoma Within Multiple Datasets.DOCX by Mingwei Zhang (661218)

Table6_Prognostic Value of mRNAsi/Corrected mRNAsi Calculated by the One-Class Logistic Regression Machine-Learning Algorithm in Glioblastoma Within Multiple Datasets.DOCX by Mingwei Zhang (661218)

Consistency of model-derived predictive patterns as a function of sample diversity. by Oualid Benkarim (9707986)

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

Algorithm membership function. by Mohamed Raef Smaoui (9865830)

ROC analysis of the Machine Learning Algorithm. by Stephan Ellmann (314565)

Convergence curves of different algorithms on the benchmark functions. by Aihua Guo (13267712)

WGCNA and machine learning algorithms. by Shushu Wang (6870191)

Super.Complex identifies likely protein complexes within a PPI network using a distributed supervised AutoML method. by Meghana Venkata Palukuri (11890672)

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Out-of-distribution prediction and performance of predictive models as a function of sample diversity. by Oualid Benkarim (9707986)

DataSheet5_Prognostic Value of mRNAsi/Corrected mRNAsi Calculated by the One-Class Logistic Regression Machine-Learning Algorithm in Glioblastoma Within Multiple Datasets.PDF by Mingwei Zhang (661218)