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trainscg (scaled conjugate gradient backpropagation)  (MathWorks Inc)


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    MathWorks Inc trainscg (scaled conjugate gradient backpropagation)
    Trainscg (Scaled Conjugate Gradient Backpropagation), supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/trainscg+(scaled+conjugate+gradient+backpropagation)/pmc11593856-86-7-11
    Average 90 stars, based on 1 article reviews
    trainscg (scaled conjugate gradient backpropagation) - by Bioz Stars, 2026-09
    90/100 stars

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    Article Title: Morphology-based Prediction of Cancer Cell Migration Using an Artificial Neural Network and a Random Decision Forest
    Article Snippet: Scaled conjugate gradient backpropagation (“trainscg” in MATLAB) was used as our training function with the intention to reduce the mean square error.

    Article Title: Detecting Prostate Cancer Using Pattern Recognition Neural Networks With Flow Cytometry-Based Immunophenotyping in At-Risk Men.
    Article Snippet: Next, a scaled conjugate gradient backpropagation algorithm [trainscg()] was selected for PRNN training using the MATLAB Deep Learning Toolbox (Version 12.1 R2019a).

    Article Title: Can (should) theories of crowding be unified?
    Article Snippet: We trained the network using the scaled conjugate gradient backpropagation algorithm (“trainscg” training function in MATLAB) with the blurry versions of the original images and made sure that the network achieved 100% classification performance for identifying the orientation of the target images, analogous to a human observer viewing the stimuli foveally with unlimited time.

    Article Title: Gamma band alterations and REM-like traits underpin the acute effect of the atypical psychedelic ibogaine
    Article Snippet: The training was performed employing the scaled conjugate gradient backpropagation algorithm ( trainscg built-in function in Matlab), and the performance of the network was evaluated by the cross-entropy algorithm ( crossentropy built-in function in Matlab).



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