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machine learning tool box  (MathWorks Inc)


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    MathWorks Inc machine learning tool box
    Machine Learning Tool Box, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 96/100, based on 2336 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/machine+learning+tool+box/Statistics+and+Machine+Learning+Toolbox/ppr0725613-99-2-1
    Average 96 stars, based on 2336 article reviews
    machine learning tool box - by Bioz Stars, 2026-10
    96/100 stars

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    Related Articles

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    Software:

    Article Title: Advanced Polymeric Physical Unclonable Functions: From Mechanistic Design and Computer Vision to Enhanced Effect of Stimuli.
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    other:

    Article Title: Pharmacokinetic modelling during long-term anesthesia: minimizing the gap
    Article Snippet: All these tools were used from the Statistics and Machine Learning Toolbox® in MATLAB®.

    Article Title: Dynamic modulation of social gaze by sex and familiarity in marmoset dyads
    Article Snippet: We used the maximum likelihood estimation method (mle() function in the Statistics and Machine Learning Toolbox in MATLAB) to fit a mixture of Gamma and Gaussian distributions.

    Article Title: Light-induced 3D-printing of DNA-based responsive hydrogels
    Article Snippet: An open-source algorithm has been used for the Shapiro-Wilk’s test [49], while the Student tests were picked from Statistics and Machine Learning Toolbox (MATLAB).



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    Image Search Results


    Voltage U—RMSE: D-PNN = 1.153, SMLT (Tree) = 1.118 [V], 12 inputs + THDU (both D-PNN and SMLT) in the 2nd stage.

    Journal: Scientific Reports

    Article Title: Power quality approximation for household equipment load combinations using a stepwise growth in input parameters of AI models

    doi: 10.1038/s41598-022-21812-1

    Figure Lengend Snippet: Voltage U—RMSE: D-PNN = 1.153, SMLT (Tree) = 1.118 [V], 12 inputs + THDU (both D-PNN and SMLT) in the 2nd stage.

    Article Snippet: [A] Matlab—Statistics and Machine Learning tool-box for regression (SMLT) www.mathworks.com/help/stats/choose-regression-model-options.html . https://mathworks.com/help/stats/select-data-and-validation-for-regression-problem.html .

    Techniques:

    Power P—RMSE: D-PNN = 0.177, SMLT (GPR) = 0.182 [kW], 12 inputs + U + PF (D-PNN), 12 inputs + PF + THDU (SMLT) in the 3rd stage.

    Journal: Scientific Reports

    Article Title: Power quality approximation for household equipment load combinations using a stepwise growth in input parameters of AI models

    doi: 10.1038/s41598-022-21812-1

    Figure Lengend Snippet: Power P—RMSE: D-PNN = 0.177, SMLT (GPR) = 0.182 [kW], 12 inputs + U + PF (D-PNN), 12 inputs + PF + THDU (SMLT) in the 3rd stage.

    Article Snippet: [A] Matlab—Statistics and Machine Learning tool-box for regression (SMLT) www.mathworks.com/help/stats/choose-regression-model-options.html . https://mathworks.com/help/stats/select-data-and-validation-for-regression-problem.html .

    Techniques:

    THDU—RMSE: D-PNN = 0.429, SMLT (Tree) = 0.443 [%], 12 inputs + U (both D-PNN and SMLT) in the 2nd stage.

    Journal: Scientific Reports

    Article Title: Power quality approximation for household equipment load combinations using a stepwise growth in input parameters of AI models

    doi: 10.1038/s41598-022-21812-1

    Figure Lengend Snippet: THDU—RMSE: D-PNN = 0.429, SMLT (Tree) = 0.443 [%], 12 inputs + U (both D-PNN and SMLT) in the 2nd stage.

    Article Snippet: [A] Matlab—Statistics and Machine Learning tool-box for regression (SMLT) www.mathworks.com/help/stats/choose-regression-model-options.html . https://mathworks.com/help/stats/select-data-and-validation-for-regression-problem.html .

    Techniques:

    Power Factor PF—RMSE: D-PNN = 0.0516, SMLT (GPR) = 0.0496 [], 12 inputs + Pst + U (D-PNN, 12 inputs + Pst + THDU (SMLT) in the 3rd stage.

    Journal: Scientific Reports

    Article Title: Power quality approximation for household equipment load combinations using a stepwise growth in input parameters of AI models

    doi: 10.1038/s41598-022-21812-1

    Figure Lengend Snippet: Power Factor PF—RMSE: D-PNN = 0.0516, SMLT (GPR) = 0.0496 [], 12 inputs + Pst + U (D-PNN, 12 inputs + Pst + THDU (SMLT) in the 3rd stage.

    Article Snippet: [A] Matlab—Statistics and Machine Learning tool-box for regression (SMLT) www.mathworks.com/help/stats/choose-regression-model-options.html . https://mathworks.com/help/stats/select-data-and-validation-for-regression-problem.html .

    Techniques:

    Pst—RMSE: D-PNN = 0.811, SMLT (EBoosT) = 0.544 [], 12 inputs + Pst (both D-PNN and SMLT) in the 2nd stage.

    Journal: Scientific Reports

    Article Title: Power quality approximation for household equipment load combinations using a stepwise growth in input parameters of AI models

    doi: 10.1038/s41598-022-21812-1

    Figure Lengend Snippet: Pst—RMSE: D-PNN = 0.811, SMLT (EBoosT) = 0.544 [], 12 inputs + Pst (both D-PNN and SMLT) in the 2nd stage.

    Article Snippet: [A] Matlab—Statistics and Machine Learning tool-box for regression (SMLT) www.mathworks.com/help/stats/choose-regression-model-options.html . https://mathworks.com/help/stats/select-data-and-validation-for-regression-problem.html .

    Techniques:

    Voltage U 3-step model estimations.

    Journal: Scientific Reports

    Article Title: Power quality approximation for household equipment load combinations using a stepwise growth in input parameters of AI models

    doi: 10.1038/s41598-022-21812-1

    Figure Lengend Snippet: Voltage U 3-step model estimations.

    Article Snippet: [A] Matlab—Statistics and Machine Learning tool-box for regression (SMLT) www.mathworks.com/help/stats/choose-regression-model-options.html . https://mathworks.com/help/stats/select-data-and-validation-for-regression-problem.html .

    Techniques:

    Power P 3-step model estimations.

    Journal: Scientific Reports

    Article Title: Power quality approximation for household equipment load combinations using a stepwise growth in input parameters of AI models

    doi: 10.1038/s41598-022-21812-1

    Figure Lengend Snippet: Power P 3-step model estimations.

    Article Snippet: [A] Matlab—Statistics and Machine Learning tool-box for regression (SMLT) www.mathworks.com/help/stats/choose-regression-model-options.html . https://mathworks.com/help/stats/select-data-and-validation-for-regression-problem.html .

    Techniques:

    THDU 3-step model estimations.

    Journal: Scientific Reports

    Article Title: Power quality approximation for household equipment load combinations using a stepwise growth in input parameters of AI models

    doi: 10.1038/s41598-022-21812-1

    Figure Lengend Snippet: THDU 3-step model estimations.

    Article Snippet: [A] Matlab—Statistics and Machine Learning tool-box for regression (SMLT) www.mathworks.com/help/stats/choose-regression-model-options.html . https://mathworks.com/help/stats/select-data-and-validation-for-regression-problem.html .

    Techniques:

    Power Factor PF 3-step model estimations.

    Journal: Scientific Reports

    Article Title: Power quality approximation for household equipment load combinations using a stepwise growth in input parameters of AI models

    doi: 10.1038/s41598-022-21812-1

    Figure Lengend Snippet: Power Factor PF 3-step model estimations.

    Article Snippet: [A] Matlab—Statistics and Machine Learning tool-box for regression (SMLT) www.mathworks.com/help/stats/choose-regression-model-options.html . https://mathworks.com/help/stats/select-data-and-validation-for-regression-problem.html .

    Techniques:

    Pst 3-step model estimations.

    Journal: Scientific Reports

    Article Title: Power quality approximation for household equipment load combinations using a stepwise growth in input parameters of AI models

    doi: 10.1038/s41598-022-21812-1

    Figure Lengend Snippet: Pst 3-step model estimations.

    Article Snippet: [A] Matlab—Statistics and Machine Learning tool-box for regression (SMLT) www.mathworks.com/help/stats/choose-regression-model-options.html . https://mathworks.com/help/stats/select-data-and-validation-for-regression-problem.html .

    Techniques: