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  2. Principal component analysis - Wikipedia

    en.wikipedia.org/wiki/Principal_component_analysis

    Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data preprocessing.. The data is linearly transformed onto a new coordinate system such that the directions (principal components) capturing the largest variation in the data can be easily identified.

  3. Scree plot - Wikipedia

    en.wikipedia.org/wiki/Scree_plot

    In multivariate statistics, a scree plot is a line plot of the eigenvalues of factors or principal components in an analysis. [1] The scree plot is used to determine the number of factors to retain in an exploratory factor analysis (FA) or principal components to keep in a principal component analysis (PCA).

  4. Kernel principal component analysis - Wikipedia

    en.wikipedia.org/wiki/Kernel_principal_component...

    Output after kernel PCA, with a Gaussian kernel. Note in particular that the first principal component is enough to distinguish the three different groups, which is impossible using only linear PCA, because linear PCA operates only in the given (in this case two-dimensional) space, in which these concentric point clouds are not linearly separable.

  5. ANOVA–simultaneous component analysis - Wikipedia

    en.wikipedia.org/wiki/ANOVA–simultaneous...

    Simultaneous component analysis is mathematically identical to PCA, but is semantically different in that it models different objects or subjects at the same time. The standard notation for a SCA – and PCA – model is: = ′ + where X is the data, T are the component scores and P are the component loadings.

  6. Data and information visualization - Wikipedia

    en.wikipedia.org/wiki/Data_and_information...

    The most fundamental data analysis approaches are visualization (histograms, scatter plots, surface plots, tree maps, parallel coordinate plots, etc.), statistics (hypothesis test, regression, PCA, etc.), data mining (association mining, etc.), and machine learning methods (clustering, classification, decision trees, etc.). Among these ...

  7. Google Charts - Wikipedia

    en.wikipedia.org/wiki/Google_Charts

    Google Charts is an online tool that is used to create charts and graphs. It uses HTML5 and SVG to function on multiple browsers and devices without extra plugins or software. It is known for its wide range of chart options and features, which are explained on the official Google Charts website. [1]

  8. The Federal Reserve’s latest dot plot, explained — and what ...

    www.aol.com/finance/federal-latest-dot-plot...

    The Fed’s dot plot is a chart updated quarterly that records each Fed official’s projection for the central bank’s key short-term interest rate, the federal funds rate. The dots reflect what ...

  9. Google Chart API - Wikipedia

    en.wikipedia.org/wiki/Google_Chart_API

    The Google Chart API is a non-interactive Web service (now deprecated) that creates graphical charts from user-supplied data. Google servers create a PNG image of a chart from data and formatting parameters specified by a user's HTTP request. The service supports a wide variety of chart information and formatting.