Search alternatives:
model optimization » codon optimization (Expand Search), global optimization (Expand Search), wolf optimization (Expand Search)
based optimization » whale optimization (Expand Search)
binary sample » final sample (Expand Search), binary people (Expand Search), intra sample (Expand Search)
binary naive » binary pairs (Expand Search)
sample based » samples based (Expand Search), scale based (Expand Search)
naive model » canine model (Expand Search)
model optimization » codon optimization (Expand Search), global optimization (Expand Search), wolf optimization (Expand Search)
based optimization » whale optimization (Expand Search)
binary sample » final sample (Expand Search), binary people (Expand Search), intra sample (Expand Search)
binary naive » binary pairs (Expand Search)
sample based » samples based (Expand Search), scale based (Expand Search)
naive model » canine model (Expand Search)
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Effects of Class Imbalance and Data Scarcity on the Performance of Binary Classification Machine Learning Models Developed Based on ToxCast/Tox21 Assay Data
Published 2022“…An assay matrix based on CI and DS was prepared for 335 assays with biologically intended target information, and 28 CI assays and 3 DS assays were selected. Thirty models established by combining five molecular fingerprints (i.e., Morgan, MACCS, RDKit, Pattern, and Layered) and six algorithms [i.e., gradient boosting tree, random forest (RF), multi-layered perceptron, <i>k</i>-nearest neighbor, logistic regression, and naive Bayes] were trained using the selected assay data set. …”
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ROC curve for binary classification.
Published 2024“…Specifically, an image enhancement algorithm based on histogram equalization and bilateral filtering techniques was deployed to reduce noise and enhance the quality of the images. …”
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Confusion matrix for binary classification.
Published 2024“…Specifically, an image enhancement algorithm based on histogram equalization and bilateral filtering techniques was deployed to reduce noise and enhance the quality of the images. …”
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Identification and quantitation of clinically relevant microbes in patient samples: Comparison of three k-mer based classifiers for speed, accuracy, and sensitivity
Published 2019“…We tested the accuracy, sensitivity, and resource requirements of three top metagenomic taxonomic classifiers that use fast k-mer based algorithms: Centrifuge, CLARK, and KrakenUniq. …”
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Triplet Matching for Estimating Causal Effects With Three Treatment Arms: A Comparative Study of Mortality by Trauma Center Level
Published 2021“…Our algorithm outperforms the nearest neighbor algorithm and is shown to produce matched samples with total distance no larger than twice the optimal distance. …”
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Testing results for classifying AD, MCI and NC.
Published 2024“…Specifically, an image enhancement algorithm based on histogram equalization and bilateral filtering techniques was deployed to reduce noise and enhance the quality of the images. …”
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Summary of existing CNN models.
Published 2024“…Specifically, an image enhancement algorithm based on histogram equalization and bilateral filtering techniques was deployed to reduce noise and enhance the quality of the images. …”
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Parameter settings.
Published 2024“…<div><p>Differential Evolution (DE) is widely recognized as a highly effective evolutionary algorithm for global optimization. It has proven its efficacy in tackling diverse problems across various fields and real-world applications. …”
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Data_Sheet_1_A real-time driver fatigue identification method based on GA-GRNN.ZIP
Published 2022“…In this paper, a non-invasive and low-cost method of fatigue driving state identification based on genetic algorithm optimization of generalized regression neural network model is proposed. …”