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built-in matlab functions lda  (MathWorks Inc)


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    MathWorks Inc built-in matlab functions lda
    Mean risks and RMS for model 1, three classification rules <t>(LDA,</t> <t>QDA,</t> and OBRC), and all risk estimators. a Mean risk under LDA; b RMS risk under LDA; c mean risk under QDA; d RMS risk under QDA; e mean risk under OBRC; f RMS risk under OBRC
    Built In Matlab Functions Lda, 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/built-in matlab functions lda/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    built-in matlab functions lda - by Bioz Stars, 2026-03
    90/100 stars

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    1) Product Images from "On optimal Bayesian classification and risk estimation under multiple classes"

    Article Title: On optimal Bayesian classification and risk estimation under multiple classes

    Journal: EURASIP Journal on Bioinformatics and Systems Biology

    doi: 10.1186/s13637-015-0028-3

    Mean risks and RMS for model 1, three classification rules (LDA, QDA, and OBRC), and all risk estimators. a Mean risk under LDA; b RMS risk under LDA; c mean risk under QDA; d RMS risk under QDA; e mean risk under OBRC; f RMS risk under OBRC
    Figure Legend Snippet: Mean risks and RMS for model 1, three classification rules (LDA, QDA, and OBRC), and all risk estimators. a Mean risk under LDA; b RMS risk under LDA; c mean risk under QDA; d RMS risk under QDA; e mean risk under OBRC; f RMS risk under OBRC

    Techniques Used:

    Mean risks and RMS for model 2, three classification rules (LDA, QDA, and OBRC), and all risk estimators. a Mean risk under LDA; b RMS risk under LDA; c mean risk under QDA; d RMS risk under QDA; e mean risk under OBRC; f RMS risk under OBRC
    Figure Legend Snippet: Mean risks and RMS for model 2, three classification rules (LDA, QDA, and OBRC), and all risk estimators. a Mean risk under LDA; b RMS risk under LDA; c mean risk under QDA; d RMS risk under QDA; e mean risk under OBRC; f RMS risk under OBRC

    Techniques Used:

    Example decision boundaries for model 3 with multi-class classification. a LDA; b QDA; c OBRC; d L-SVM; e RBF-SVM
    Figure Legend Snippet: Example decision boundaries for model 3 with multi-class classification. a LDA; b QDA; c OBRC; d L-SVM; e RBF-SVM

    Techniques Used:

    Example decision boundaries for model 4 with multi-class classification. a LDA; b QDA; c OBRC; d L-SVM; e RBF-SVM
    Figure Legend Snippet: Example decision boundaries for model 4 with multi-class classification. a LDA; b QDA; c OBRC; d L-SVM; e RBF-SVM

    Techniques Used:

    True risk statistics for models 3 and 4 and five classification rules (LDA, QDA, OBRC, L-SVM, and RBF-SVM). a Model 3, mean; b model 3, standard deviation; c model 4, mean; d model 4, standard deviation
    Figure Legend Snippet: True risk statistics for models 3 and 4 and five classification rules (LDA, QDA, OBRC, L-SVM, and RBF-SVM). a Model 3, mean; b model 3, standard deviation; c model 4, mean; d model 4, standard deviation

    Techniques Used: Standard Deviation

    True risk statistics for models 7 and 8 and five classification rules (LDA, QDA, OBRC, L-SVM, and RBF-SVM). a Model 7, mean; b model 7, standard deviation; c model 8, mean; d model 8, standard deviation
    Figure Legend Snippet: True risk statistics for models 7 and 8 and five classification rules (LDA, QDA, OBRC, L-SVM, and RBF-SVM). a Model 7, mean; b model 7, standard deviation; c model 8, mean; d model 8, standard deviation

    Techniques Used: Standard Deviation

    Mean risks, RMS, and Q–Q plots of Z for the breast cancer dataset, D =2, three classification rules (LDA, QDA, and OBRC), and all risk estimators. a Mean risk under LDA; b RMS risk under LDA; c Q–Q plots of Z under LDA; d mean risk under QDA; e RMS risk under QDA; f Q–Q plots of Z under QDA; g mean risk under OBRC; h RMS risk under OBRC; i Q–Q plots of Z under OBRC
    Figure Legend Snippet: Mean risks, RMS, and Q–Q plots of Z for the breast cancer dataset, D =2, three classification rules (LDA, QDA, and OBRC), and all risk estimators. a Mean risk under LDA; b RMS risk under LDA; c Q–Q plots of Z under LDA; d mean risk under QDA; e RMS risk under QDA; f Q–Q plots of Z under QDA; g mean risk under OBRC; h RMS risk under OBRC; i Q–Q plots of Z under OBRC

    Techniques Used:

    Mean risks, RMS and Q–Q plots of Z for the breast cancer dataset, D =5, three classification rules (LDA, QDA, and OBRC), and all risk estimators. a Mean risk under LDA; b RMS risk under LDA; c Q-Q plots of Z under LDA; d mean risk under QDA; e RMS risk under QDA; f Q–Q plots of Z under QDA; g mean risk under OBRC; h RMS risk under OBRC; i Q–Q plots of Z under OBRC
    Figure Legend Snippet: Mean risks, RMS and Q–Q plots of Z for the breast cancer dataset, D =5, three classification rules (LDA, QDA, and OBRC), and all risk estimators. a Mean risk under LDA; b RMS risk under LDA; c Q-Q plots of Z under LDA; d mean risk under QDA; e RMS risk under QDA; f Q–Q plots of Z under QDA; g mean risk under OBRC; h RMS risk under OBRC; i Q–Q plots of Z under OBRC

    Techniques Used:

    True risk mean for the TCGA dataset and five classification rules (LDA, QDA, OBRC, L-SVM, and RBF-SVM). a FS-1, D =2; b FS-2, D =2; c FS-1, D =5; d FS-2, D =5; e FS-1, D =20; f FS-2, D =20
    Figure Legend Snippet: True risk mean for the TCGA dataset and five classification rules (LDA, QDA, OBRC, L-SVM, and RBF-SVM). a FS-1, D =2; b FS-2, D =2; c FS-1, D =5; d FS-2, D =5; e FS-1, D =20; f FS-2, D =20

    Techniques Used:



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    built-in matlab functions lda  (MathWorks Inc)
    90
    MathWorks Inc built-in matlab functions lda
    Mean risks and RMS for model 1, three classification rules <t>(LDA,</t> <t>QDA,</t> and OBRC), and all risk estimators. a Mean risk under LDA; b RMS risk under LDA; c mean risk under QDA; d RMS risk under QDA; e mean risk under OBRC; f RMS risk under OBRC
    Built In Matlab Functions Lda, 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/built-in matlab functions lda/product/MathWorks Inc
    Average 90 stars, based on 1 article reviews
    built-in matlab functions lda - by Bioz Stars, 2026-03
    90/100 stars
    		  Buy from Supplier

    Image Search Results


    Mean risks and RMS for model 1, three classification rules (LDA, QDA, and OBRC), and all risk estimators. a Mean risk under LDA; b RMS risk under LDA; c mean risk under QDA; d RMS risk under QDA; e mean risk under OBRC; f RMS risk under OBRC

    Journal: EURASIP Journal on Bioinformatics and Systems Biology

    Article Title: On optimal Bayesian classification and risk estimation under multiple classes

    doi: 10.1186/s13637-015-0028-3

    Figure Lengend Snippet: Mean risks and RMS for model 1, three classification rules (LDA, QDA, and OBRC), and all risk estimators. a Mean risk under LDA; b RMS risk under LDA; c mean risk under QDA; d RMS risk under QDA; e mean risk under OBRC; f RMS risk under OBRC

    Article Snippet: We used built-in MATLAB functions to implement LDA and QDA.

    Techniques:

    Mean risks and RMS for model 2, three classification rules (LDA, QDA, and OBRC), and all risk estimators. a Mean risk under LDA; b RMS risk under LDA; c mean risk under QDA; d RMS risk under QDA; e mean risk under OBRC; f RMS risk under OBRC

    Journal: EURASIP Journal on Bioinformatics and Systems Biology

    Article Title: On optimal Bayesian classification and risk estimation under multiple classes

    doi: 10.1186/s13637-015-0028-3

    Figure Lengend Snippet: Mean risks and RMS for model 2, three classification rules (LDA, QDA, and OBRC), and all risk estimators. a Mean risk under LDA; b RMS risk under LDA; c mean risk under QDA; d RMS risk under QDA; e mean risk under OBRC; f RMS risk under OBRC

    Article Snippet: We used built-in MATLAB functions to implement LDA and QDA.

    Techniques:

    Example decision boundaries for model 3 with multi-class classification. a LDA; b QDA; c OBRC; d L-SVM; e RBF-SVM

    Journal: EURASIP Journal on Bioinformatics and Systems Biology

    Article Title: On optimal Bayesian classification and risk estimation under multiple classes

    doi: 10.1186/s13637-015-0028-3

    Figure Lengend Snippet: Example decision boundaries for model 3 with multi-class classification. a LDA; b QDA; c OBRC; d L-SVM; e RBF-SVM

    Article Snippet: We used built-in MATLAB functions to implement LDA and QDA.

    Techniques:

    Example decision boundaries for model 4 with multi-class classification. a LDA; b QDA; c OBRC; d L-SVM; e RBF-SVM

    Journal: EURASIP Journal on Bioinformatics and Systems Biology

    Article Title: On optimal Bayesian classification and risk estimation under multiple classes

    doi: 10.1186/s13637-015-0028-3

    Figure Lengend Snippet: Example decision boundaries for model 4 with multi-class classification. a LDA; b QDA; c OBRC; d L-SVM; e RBF-SVM

    Article Snippet: We used built-in MATLAB functions to implement LDA and QDA.

    Techniques:

    True risk statistics for models 3 and 4 and five classification rules (LDA, QDA, OBRC, L-SVM, and RBF-SVM). a Model 3, mean; b model 3, standard deviation; c model 4, mean; d model 4, standard deviation

    Journal: EURASIP Journal on Bioinformatics and Systems Biology

    Article Title: On optimal Bayesian classification and risk estimation under multiple classes

    doi: 10.1186/s13637-015-0028-3

    Figure Lengend Snippet: True risk statistics for models 3 and 4 and five classification rules (LDA, QDA, OBRC, L-SVM, and RBF-SVM). a Model 3, mean; b model 3, standard deviation; c model 4, mean; d model 4, standard deviation

    Article Snippet: We used built-in MATLAB functions to implement LDA and QDA.

    Techniques: Standard Deviation

    True risk statistics for models 7 and 8 and five classification rules (LDA, QDA, OBRC, L-SVM, and RBF-SVM). a Model 7, mean; b model 7, standard deviation; c model 8, mean; d model 8, standard deviation

    Journal: EURASIP Journal on Bioinformatics and Systems Biology

    Article Title: On optimal Bayesian classification and risk estimation under multiple classes

    doi: 10.1186/s13637-015-0028-3

    Figure Lengend Snippet: True risk statistics for models 7 and 8 and five classification rules (LDA, QDA, OBRC, L-SVM, and RBF-SVM). a Model 7, mean; b model 7, standard deviation; c model 8, mean; d model 8, standard deviation

    Article Snippet: We used built-in MATLAB functions to implement LDA and QDA.

    Techniques: Standard Deviation

    Mean risks, RMS, and Q–Q plots of Z for the breast cancer dataset, D =2, three classification rules (LDA, QDA, and OBRC), and all risk estimators. a Mean risk under LDA; b RMS risk under LDA; c Q–Q plots of Z under LDA; d mean risk under QDA; e RMS risk under QDA; f Q–Q plots of Z under QDA; g mean risk under OBRC; h RMS risk under OBRC; i Q–Q plots of Z under OBRC

    Journal: EURASIP Journal on Bioinformatics and Systems Biology

    Article Title: On optimal Bayesian classification and risk estimation under multiple classes

    doi: 10.1186/s13637-015-0028-3

    Figure Lengend Snippet: Mean risks, RMS, and Q–Q plots of Z for the breast cancer dataset, D =2, three classification rules (LDA, QDA, and OBRC), and all risk estimators. a Mean risk under LDA; b RMS risk under LDA; c Q–Q plots of Z under LDA; d mean risk under QDA; e RMS risk under QDA; f Q–Q plots of Z under QDA; g mean risk under OBRC; h RMS risk under OBRC; i Q–Q plots of Z under OBRC

    Article Snippet: We used built-in MATLAB functions to implement LDA and QDA.

    Techniques:

    Mean risks, RMS and Q–Q plots of Z for the breast cancer dataset, D =5, three classification rules (LDA, QDA, and OBRC), and all risk estimators. a Mean risk under LDA; b RMS risk under LDA; c Q-Q plots of Z under LDA; d mean risk under QDA; e RMS risk under QDA; f Q–Q plots of Z under QDA; g mean risk under OBRC; h RMS risk under OBRC; i Q–Q plots of Z under OBRC

    Journal: EURASIP Journal on Bioinformatics and Systems Biology

    Article Title: On optimal Bayesian classification and risk estimation under multiple classes

    doi: 10.1186/s13637-015-0028-3

    Figure Lengend Snippet: Mean risks, RMS and Q–Q plots of Z for the breast cancer dataset, D =5, three classification rules (LDA, QDA, and OBRC), and all risk estimators. a Mean risk under LDA; b RMS risk under LDA; c Q-Q plots of Z under LDA; d mean risk under QDA; e RMS risk under QDA; f Q–Q plots of Z under QDA; g mean risk under OBRC; h RMS risk under OBRC; i Q–Q plots of Z under OBRC

    Article Snippet: We used built-in MATLAB functions to implement LDA and QDA.

    Techniques:

    True risk mean for the TCGA dataset and five classification rules (LDA, QDA, OBRC, L-SVM, and RBF-SVM). a FS-1, D =2; b FS-2, D =2; c FS-1, D =5; d FS-2, D =5; e FS-1, D =20; f FS-2, D =20

    Journal: EURASIP Journal on Bioinformatics and Systems Biology

    Article Title: On optimal Bayesian classification and risk estimation under multiple classes

    doi: 10.1186/s13637-015-0028-3

    Figure Lengend Snippet: True risk mean for the TCGA dataset and five classification rules (LDA, QDA, OBRC, L-SVM, and RBF-SVM). a FS-1, D =2; b FS-2, D =2; c FS-1, D =5; d FS-2, D =5; e FS-1, D =20; f FS-2, D =20

    Article Snippet: We used built-in MATLAB functions to implement LDA and QDA.

    Techniques: