<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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Sensitivity values of IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

Specificity values of IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

Fitness values of IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

Number of features selected for IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

Classification accuracy values of IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

F-score values of IRBMO vs. other binary algorithms. by Chenyi Zhu (9383370)

Numerical example for determining the optimal number of clusters in Algorithm 2. by Yi Wei Tye (22208735)

Face recognition algorithm flow based on the PCA. by Na Lin (69470)

Binary contingency table. by Lu Xiao (314030)

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

“…The MapReduce parallel programming model on the Hadoop platform is used to perform an adaptive fusion of hue, local binary pattern (LBP) and scale-invariant feature transform (SIFT) features extracted from images to derive optimal combinations of weights. …”

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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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)

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

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Top-performing model configuration and performance by algorithm type. by Uğur Ejder (22683228)

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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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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. …”