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)

<i>De Novo</i> Drug Design of Targeted Chemical Libraries Based on Artificial Intelligence and Pair-Based Multiobjective Optimization by Alberga Domenico (9356272)

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Train test validation libraries. by Muhammad Usman Tariq (11022141)

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S1 Data - by Guangwei Liu (181992)

“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”

ReaLigands: A Ligand Library Cultivated from Experiment and Intended for Molecular Computational Catalyst Design by Shu-Sen Chen (1777108)

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Parameter settings for algorithms. by Guangwei Liu (181992)

“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”

Parameter settings for algorithms. by Guangwei Liu (181992)

“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”

Average runtime of different algorithms. by Guangwei Liu (181992)

“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”

Average runtime of different algorithms. by Guangwei Liu (181992)

“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”

Flowchart of GJO-GWO algorithm. by Guangwei Liu (181992)

“…<div><p>This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). …”

RosettaAMRLD: A Reaction-Driven Approach for Structure-Based Drug Design from Combinatorial Libraries with Monte Carlo Metropolis Algorithms by Yidan Tang (6623693)

“…The Rosetta automated Monte Carlo reaction-based ligand design (RosettaAMRLD) integrates a Monte Carlo Metropolis (MCM) algorithm and reaction-driven molecule proposal to enhance structure-based <i>de novo</i> drug discovery. …”

Summary of classification algorithms. by Stephen R. Piccolo (8367780)

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Classification algorithm hyperparameter combinations. by Stephen R. Piccolo (8367780)

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Summary of feature-selection algorithms. by Stephen R. Piccolo (8367780)

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Feature-selection algorithm hyperparameter combinations. by Stephen R. Piccolo (8367780)

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A Practical Algorithm to Solve the Near-Congruence Problem for Rigid Molecules and Clusters by José Manuel Vásquez-Pérez (12843737)

“…The Fortran implementation of the algorithm is available as an open source library (https://github.com/qcuaeh/molalignlib) and is suitable to be used in global optimization methods for the identification of local minima or basins.…”

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

“…Secondly, based on the data libraries of the IPMMPO, two tuple sets suitable for constraint programming modeling are further designed as data preprocessing. …”

Comparison of ranks for classification algorithms across performance metrics. by Stephen R. Piccolo (8367780)

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Tradeoff between execution time and predictive performance for classification algorithms. by Stephen R. Piccolo (8367780)

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Relative classification performance per combination of feature-selection and classification algorithm. by Stephen R. Piccolo (8367780)

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