Showing 6 open source projects for "hierarchical clustering in matlab"

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  • 1
    Orange Data Mining

    Orange Data Mining

    Orange: Interactive data analysis

    ...Perform simple data analysis with clever data visualization. Explore statistical distributions, box plots and scatter plots, or dive deeper with decision trees, hierarchical clustering, heatmaps, MDS and linear projections. Even your multidimensional data can become sensible in 2D, especially with clever attribute ranking and selections. Interactive data exploration for rapid qualitative analysis with clean visualizations. Graphic user interface allows you to focus on exploratory data analysis instead of coding, while clever defaults make fast prototyping of a data analysis workflow extremely easy. ...
    Downloads: 81 This Week
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  • 2
    NOVA

    NOVA

    Analysis and visualization of complexome profiling data.

    NOVA is a program designed to analysis complexome profiling data (Heide et al., 2012). A graphical user interface (GUI) provides various visualization tools, such as heat maps and 2D plots. Several hierarchical clustering algorithms (e.g., single linkage, average linkage, Wards linkage), different distance measures (e.g., Euclidean distance, Manhattan distance, Pearson distance), and various normalization techniques are implemented. Many additional functions like zooming, searching for proteins, image export, and automatic file format recognition support intuitive handling for biologists. ...
    Downloads: 9 This Week
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  • 3
    Visualization and clustering analysis of X-Ray diffraction data from combinatorial thin film libraries.
    Downloads: 0 This Week
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  • 4
    The final build of this software now is distributed in R, embedded in "RedeR': an R/Bioconductor package for hierarchical and nested network analysis... more about RedeR: http://bioconductor.org/packages/2.9/bioc/html/RedeR.html
    Downloads: 0 This Week
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  • 5
    The Databionics ESOM Tools offer many data mining tasks using Emergent Self-Organizing Maps. Visualization, clustering, and classification of high-dimensional data using databionics principles can be performed interactively or automatically.
    Downloads: 0 This Week
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  • 6
    rendering flow maps with hierarchical clustering.
    Downloads: 0 This Week
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