FeatureSpacePlot

FeatureSpacePlot[{example1,example2,}]

plots features extracted from the examplei as a scatter plot.

Details and Options

  • FeatureSpacePlot can be used on many types of data, including numerical, textual, sounds and images, and combinations of these.
  • Each examplei can be a single data element, a list of data elements, an association of data elements, or a Dataset object.
  • The following wrappers w can be used for the examplei:
  • Annotation[datai,label]provide an annotation for the data
    Button[datai,action]define an action to execute when the data is clicked
    Callout[datai,label]label the data with a callout
    Callout[datai,label,pos]place the callout at relative position pos
    EventHandler[datai,]define a general event handler for the data
    Hyperlink[datai,uri]make the data a hyperlink
    Labeled[datai,label]label the data
    Labeled[datai,label,pos]place the label at relative position pos
    Legended[datai,label]identify the data in a legend
    PopupWindow[datai,cont]attach a popup window to the data
    StatusArea[datai,label]display in the status area on mouseover
    Style[datai,styles]show the data using the specified styles
    Tooltip[datai,label]attach a tooltip to the data
    Tooltip[datai]use data values as tooltips
  • Wrappers w can be applied at multiple levels:
  • {,w[examplei],}wrap the value examplei
    w[{example1,example2,}]wrap all the examples
    w1[w2[]]use nested wrappers
  • Callout, Labeled, and Placed can use the following positions pos:
  • Automaticautomatically placed labels
    Above, Below, Before, Afterpositions around the data
    xnear the data at a position x
    Scaled[s]scaled position s along the data
    {s,Above},{s,Below},relative position at position s along the data
    {pos,epos}epos in label placed at relative position pos of the data
  • FeatureSpacePlot has the same options as Graphics, with the following additions and changes:
  • AspectRatio1ratio of height to width
    AxesFalsewhether to draw axes
    FeatureExtractorIdentityhow to extract features from which to learn
    FeatureNamesAutomaticnames to assign to elements of the examplei
    FeatureTypesAutomaticfeature types to assume for elements of the examplei
    FillingNonehow to fill in stems for each point
    FillingStyleAutomaticstyle to use for filling
    LabelingFunctionAutomatichow to label points
    MaxPlotPointsAutomaticthe maximum number of points to include
    PerformanceGoal$PerformanceGoalaspects of performance to try to optimize
    PlotLabelNoneoverall label for the plot
    PlotLabelsNonelabels for data
    PlotLegendsNonelegends for data
    PlotMarkersNonemarkers to use to indicate each point
    PlotRangeAutomaticrange of values to include
    PlotRangeClippingTruewhether to clip at the plot range
    PlotStyleAutomaticgraphics directives to determine styles of points
    PlotTheme$PlotThemeoverall theme for the plot
  • LabelingFunction->f specifies that each point should have a label given by f[value,index,lbls], where value is the value associated with the point, index is its position in the data and lbls is the list of relevant labels.
  • Possible settings for Method include:
  • Automaticautomatically chosen method
    "LatentSemanticAnalysis"latent semantic analysis method
    "Linear"automatically choose the best linear method
    "LowRankMatrixFactorization"use a low-rank matrix factorization algorithm
    "PrincipalComponentsAnalysis"principal components analysis method
    "TSNE"t-distributed stochastic neighbor embedding algorithm

Examples

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Basic Examples  (2)

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Plot the features extracted from images:

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Extract features from a simple dataset:

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Scope  (20)

Options  (17)

See Also

FeatureExtract  DimensionReduce  ListPlot  FeatureExtractor  FeatureExtraction

Introduced in 2017
(11.1)