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2-classification linear discriminant analysis (lda) algorithm  (MathWorks Inc)


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    MathWorks Inc 2-classification linear discriminant analysis (lda) algorithm
    2 Classification Linear Discriminant Analysis (Lda) Algorithm, 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/result/2-classification linear discriminant analysis (lda) algorithm/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    2-classification linear discriminant analysis (lda) algorithm - by Bioz Stars, 2026-05
    90/100 stars

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    2-classification linear discriminant analysis (lda) algorithm  (MathWorks Inc)
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    Cross-validation performance for the ( a ) linear discriminant analysis (LDA), ( b ) multilayer layer perceptron (MLP) and ( c ) support vector machine (SVM) classifiers

    Journal: BMC Medicine

    Article Title: Recurrence quantification analysis of resting state EEG signals in autism spectrum disorder – a systematic methodological exploration of technical and demographic confounders in the search for biomarkers

    doi: 10.1186/s12916-018-1086-7

    Figure Lengend Snippet: Cross-validation performance for the ( a ) linear discriminant analysis (LDA), ( b ) multilayer layer perceptron (MLP) and ( c ) support vector machine (SVM) classifiers

    Article Snippet: Three classification algorithms were implemented using MATLAB, namely LDA, a multilayer perceptron (MLP) neural network with nine nodes in one hidden layer, using the scaled conjugate gradient backpropagation training algorithm, and a support vector machine (SVM) with a nonlinear radial basis function kernel.

    Techniques: Biomarker Discovery, Plasmid Preparation

    Repeatability analysis for the ( a ) linear discriminant analysis (LDA), ( b ) multilayer layer perceptron (MLP) and ( c ) support vector machine (SVM) classifiers for age-matched sample cross-validation run 1

    Journal: BMC Medicine

    Article Title: Recurrence quantification analysis of resting state EEG signals in autism spectrum disorder – a systematic methodological exploration of technical and demographic confounders in the search for biomarkers

    doi: 10.1186/s12916-018-1086-7

    Figure Lengend Snippet: Repeatability analysis for the ( a ) linear discriminant analysis (LDA), ( b ) multilayer layer perceptron (MLP) and ( c ) support vector machine (SVM) classifiers for age-matched sample cross-validation run 1

    Article Snippet: Three classification algorithms were implemented using MATLAB, namely LDA, a multilayer perceptron (MLP) neural network with nine nodes in one hidden layer, using the scaled conjugate gradient backpropagation training algorithm, and a support vector machine (SVM) with a nonlinear radial basis function kernel.

    Techniques: Plasmid Preparation, Biomarker Discovery

    Repeatability analysis for the ( a ) linear discriminant analysis (LDA), ( b ) multilayer layer perceptron (MLP) and ( c ) support vector machine (SVM) classifiers for age-matched sample leave-one-subject-out analysis

    Journal: BMC Medicine

    Article Title: Recurrence quantification analysis of resting state EEG signals in autism spectrum disorder – a systematic methodological exploration of technical and demographic confounders in the search for biomarkers

    doi: 10.1186/s12916-018-1086-7

    Figure Lengend Snippet: Repeatability analysis for the ( a ) linear discriminant analysis (LDA), ( b ) multilayer layer perceptron (MLP) and ( c ) support vector machine (SVM) classifiers for age-matched sample leave-one-subject-out analysis

    Article Snippet: Three classification algorithms were implemented using MATLAB, namely LDA, a multilayer perceptron (MLP) neural network with nine nodes in one hidden layer, using the scaled conjugate gradient backpropagation training algorithm, and a support vector machine (SVM) with a nonlinear radial basis function kernel.

    Techniques: Plasmid Preparation