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k-means matlab function  (MathWorks Inc)


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    MathWorks Inc k-means matlab function
    K Means Matlab Function, 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/matlab+function+k-means/pm40539497-141-60-62
    Average 90 stars, based on 1 article reviews
    k-means matlab function - by Bioz Stars, 2026-09
    90/100 stars

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    Related Articles

    Introduce:

    Article Title: Plasticity of muscle synergies through fractionation and merging during development and training of human runners
    Article Snippet: This clustering was performed using the Matlab function k- means (Statistics toolbox), implemented with the squared-Euclidean metric, and with the initial cluster centroid positions chosen uniformly randomly from the to-be-clustered synergy vectors.

    Article Title: Primacy of vision shapes behavioral strategies and neural substrates of spatial navigation in marmoset hippocampus.
    Article Snippet: To increase the robustness of classification in our analysis and avoid potential species-specific biases that firing rate thresholding classification could introduce (since it hasonly beenused inmacaquemonkeys), we implemented an unsupervised classification algorithm (k-means, MATLAB function k-means) using BI and average firing rate as features.We refrained fromusing other classicalmethods of classification like spikewaveformwidth since it has been shown that short-duration waveforms from neurons recorded from the hippocampus can represent axonal activity, and are not necessarily inhibitory interneurons in nature62.

    Article Title: Plasticity of muscle synergies through fractionation and merging during development and training of human runners.
    Article Snippet: This clustering was performed using the Matlab function k-means (Statistics toolbox), implemented with the squaredEuclidean metric, and with the initial cluster centroid positions chosen uniformly randomly from the to-be-clustered synergy vectors.

    Article Title: Deficits in neural encoding of speech in preterm infants.
    Article Snippet: We used the MATLAB function k-means with default parameters (the squared Euclidean distance metric and the k-means++ algorithm for cluster center initialization) which was replicated five times to achieve a stable solution (Cohen, 2017).

    Article Title: Deficits in neural encoding of speech in preterm infants
    Article Snippet: We used the MATLAB function k-means with default parameters (the squared Euclidean distance metric and the k-means++ algorithm for cluster center initialization) which was replicated five times to achieve a stable solution ( ).

    Activity Assay:

    Article Title: Plasticity of muscle synergies through fractionation and merging during development and training of human runners
    Article Snippet: This clustering was performed using the Matlab function k- means (Statistics toolbox), implemented with the squared-Euclidean metric, and with the initial cluster centroid positions chosen uniformly randomly from the to-be-clustered synergy vectors.

    Article Title: Primacy of vision shapes behavioral strategies and neural substrates of spatial navigation in marmoset hippocampus.
    Article Snippet: To increase the robustness of classification in our analysis and avoid potential species-specific biases that firing rate thresholding classification could introduce (since it hasonly beenused inmacaquemonkeys), we implemented an unsupervised classification algorithm (k-means, MATLAB function k-means) using BI and average firing rate as features.We refrained fromusing other classicalmethods of classification like spikewaveformwidth since it has been shown that short-duration waveforms from neurons recorded from the hippocampus can represent axonal activity, and are not necessarily inhibitory interneurons in nature62.

    Article Title: Plasticity of muscle synergies through fractionation and merging during development and training of human runners.
    Article Snippet: This clustering was performed using the Matlab function k-means (Statistics toolbox), implemented with the squaredEuclidean metric, and with the initial cluster centroid positions chosen uniformly randomly from the to-be-clustered synergy vectors.

    Article Title: Deficits in neural encoding of speech in preterm infants.
    Article Snippet: We used the MATLAB function k-means with default parameters (the squared Euclidean distance metric and the k-means++ algorithm for cluster center initialization) which was replicated five times to achieve a stable solution (Cohen, 2017).

    Article Title: Deficits in neural encoding of speech in preterm infants
    Article Snippet: We used the MATLAB function k-means with default parameters (the squared Euclidean distance metric and the k-means++ algorithm for cluster center initialization) which was replicated five times to achieve a stable solution ( ).



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