Box plot.
Box plot.
a data matrix of which each row will create a box plot.
the labels for each box plot.
a tuple of window frame and plot canvas which can be added other shapes.
A box plot is a convenient way of graphically depicting groups of numerical data through their five-number summaries (the smallest observation (sample minimum), lower quartile (Q1), median (Q2), upper quartile (Q3), and largest observation (sample maximum).
A box plot is a convenient way of graphically depicting groups of numerical data through their five-number summaries (the smallest observation (sample minimum), lower quartile (Q1), median (Q2), upper quartile (Q3), and largest observation (sample maximum). A box plot may also indicate which observations, if any, might be considered outliers.
Box plots can be useful to display differences between populations without making any assumptions of the underlying statistical distribution: they are non-parametric. The spacings between the different parts of the box help indicate the degree of dispersion (spread) and skewness in the data, and identify outliers.
For a data set, we construct a boxplot in the following manner:
a data matrix of which each row will create a box plot.
a tuple of window frame and plot canvas which can be added other shapes.
Contour plot.
Contour plot. A contour plot is a graphical technique for representing a 3-dimensional surface by plotting constant z slices, called contours, on a 2-dimensional format. That is, given a value for z, lines are drawn for connecting the (x, y) coordinates where that z value occurs. The contour plot is an alternative to a 3-D surface plot.
the x coordinates of the data grid of z. Must be in ascending order.
the y coordinates of the data grid of z. Must be in ascending order.
the data matrix to create contour plot.
the level values of contours.
the color for each contour level.
a tuple of window frame and plot canvas which can be added other shapes.
Contour plot.
Contour plot. A contour plot is a graphical technique for representing a 3-dimensional surface by plotting constant z slices, called contours, on a 2-dimensional format. That is, given a value for z, lines are drawn for connecting the (x, y) coordinates where that z value occurs. The contour plot is an alternative to a 3-D surface plot.
the x coordinates of the data grid of z. Must be in ascending order.
the y coordinates of the data grid of z. Must be in ascending order.
the data matrix to create contour plot.
a tuple of window frame and plot canvas which can be added other shapes.
Contour plot.
Contour plot. A contour plot is a graphical technique for representing a 3-dimensional surface by plotting constant z slices, called contours, on a 2-dimensional format. That is, given a value for z, lines are drawn for connecting the (x, y) coordinates where that z value occurs. The contour plot is an alternative to a 3-D surface plot.
the data matrix to create contour plot.
the level values of contours.
the color for each contour level.
a tuple of window frame and plot canvas which can be added other shapes.
Contour plot.
Contour plot. A contour plot is a graphical technique for representing a 3-dimensional surface by plotting constant z slices, called contours, on a 2-dimensional format. That is, given a value for z, lines are drawn for connecting the (x, y) coordinates where that z value occurs. The contour plot is an alternative to a 3-D surface plot.
the data matrix to create contour plot.
a tuple of window frame and plot canvas which can be added other shapes.
A dendrogram is a tree diagram to illustrate the arrangement of the clusters produced by hierarchical clustering.
A dendrogram is a tree diagram to illustrate the arrangement of the clusters produced by hierarchical clustering.
an n-1 by 2 matrix of which row i describes the merging of clusters at step i of the clustering. If an element j in the row is less than n, then observation j was merged at this stage. If j ≥ n then the merge was with the cluster formed at the (earlier) stage j-n of the algorithm.
a set of n-1 non-decreasing real values, which are the clustering height, i.e., the value of the criterion associated with the clustering method for the particular agglomeration.
A dendrogram is a tree diagram to illustrate the arrangement of the clusters produced by hierarchical clustering.
A dendrogram is a tree diagram to illustrate the arrangement of the clusters produced by hierarchical clustering.
hierarchical clustering object.
2D grid plot.
2D grid plot.
an m x n x 2 array which are coordinates of m x n grid.
Pseudo heat map plot.
Pseudo heat map plot.
the labels for rows of data matrix.
the labels for columns of data matrix.
a data matrix to be shown in pseudo heat map.
the color palette.
Pseudo heat map plot.
Pseudo heat map plot.
the labels for rows of data matrix.
the labels for columns of data matrix.
a data matrix to be shown in pseudo heat map.
Pseudo heat map plot.
Pseudo heat map plot.
x coordinate of data matrix cells. Must be in ascending order.
y coordinate of data matrix cells. Must be in ascending order.
a data matrix to be shown in pseudo heat map.
the color palette.
Pseudo heat map plot.
Pseudo heat map plot.
x coordinate of data matrix cells. Must be in ascending order.
y coordinate of data matrix cells. Must be in ascending order.
a data matrix to be shown in pseudo heat map.
Pseudo heat map plot.
Pseudo heat map plot.
a data matrix to be shown in pseudo heat map.
the color palette.
Pseudo heat map plot.
Pseudo heat map plot.
a data matrix to be shown in pseudo heat map.
Heat map with hex shape.
Heat map with hex shape.
the descriptions of each cell in the data matrix.
a data matrix to be shown in pseudo heat map.
the color palette.
Heat map with hex shape.
Heat map with hex shape.
the descriptions of each cell in the data matrix.
a data matrix to be shown in pseudo heat map.
Heat map with hex shape.
Heat map with hex shape.
a data matrix to be shown in pseudo heat map.
the color palette.
Heat map with hex shape.
Heat map with hex shape.
a data matrix to be shown in pseudo heat map.
3D histogram plot.
3D histogram plot.
a sample set.
the number of bins on x-axis.
the number of bins on y-axis.
3D histogram plot.
3D histogram plot.
a sample set.
the number of bins.
3D histogram plot.
3D histogram plot.
a sample set.
Histogram plot.
Histogram plot.
a sample set.
an array of size k+1 giving the breakpoints between histogram cells. Must be in ascending order.
Histogram plot.
Histogram plot.
a sample set.
the number of bins.
Histogram plot.
Histogram plot.
a sample set.
Line plot.
Line plot.
a n-by-2 or n-by-3 matrix that describes coordinates of points.
the stroke style of line.
the color of line.
the legend used to draw data points. The default value ' ' makes the point indistinguishable from the line on purpose.
a tuple of window frame and plot canvas which can be added other shapes.
Plots the regression surface.
Plots the regression surface.
training data.
response variable.
regression model.
Plots the classification boundary.
Plots the classification boundary.
training data.
training label.
classification model.
Plot a grid of scatter plots of for all attribute pairs in the attribute data of which the response variable is integer.
Plot a grid of scatter plots of for all attribute pairs in the attribute data of which the response variable is integer.
an attribute frame.
the legend for each class.
the color for each class.
the window frame.
Plot a grid of scatter plots of for all attribute pairs in the attribute data of which the response variable is integer.
Plot a grid of scatter plots of for all attribute pairs in the attribute data of which the response variable is integer.
an attribute frame.
the legend for all classes.
the color for each class.
the window frame.
Plot a grid of scatter plots of for all attribute pairs in the attribute data.
Plot a grid of scatter plots of for all attribute pairs in the attribute data.
an attribute frame.
the legend for all classes.
the window frame.
Scatter plot.
Scatter plot.
a n-by-2 or n-by-3 matrix that describes coordinates of points.
the class labels of data.
the legend for each class.
the color for each class.
a tuple of window frame and plot canvas which can be added other shapes.
Scatter plot.
Scatter plot.
a n-by-2 or n-by-3 matrix that describes coordinates of points.
the class labels of data.
the legend for all classes.
the color for each class.
a tuple of window frame and plot canvas which can be added other shapes.
Scatter plot.
Scatter plot.
a n-by-2 or n-by-3 matrix that describes coordinates of points.
labels of points.
a tuple of window frame and plot canvas which can be added other shapes.
Scatter plot.
Scatter plot.
a n-by-2 or n-by-3 matrix that describes coordinates of points.
the legend used to draw points.
the color used to draw points.
a tuple of window frame and plot canvas which can be added other shapes.
QQ plot of two sample sets.
QQ plot of two sample sets. The x-axis is the quantiles of x and the y-axis is the quantiles of y.
a sample set.
a sample set.
QQ plot of samples to given distribution.
QQ plot of samples to given distribution. The x-axis is the quantiles of x and the y-axis is the quantiles of given distribution.
a sample set.
a distribution.
QQ plot of two sample sets.
QQ plot of two sample sets. The x-axis is the quantiles of x and the y-axis is the quantiles of y.
a sample set.
a sample set.
QQ plot of samples to given distribution.
QQ plot of samples to given distribution. The x-axis is the quantiles of x and the y-axis is the quantiles of given distribution.
a sample set.
a distribution.
QQ plot of samples to standard normal distribution.
QQ plot of samples to standard normal distribution. The x-axis is the quantiles of x and the y-axis is the quantiles of normal distribution.
a sample set.
The scree plot is a useful visual aid for determining an appropriate number of principal components.
The scree plot is a useful visual aid for determining an appropriate number of principal components. The scree plot graphs the eigenvalue against the component number. To determine the appropriate number of components, we look for an "elbow" in the scree plot. The component number is taken to be the point at which the remaining eigenvalues are relatively small and all about the same size.
principal component analysis object.
Visualize sparsity pattern.
Visualize sparsity pattern.
a sparse matrix.
Create a plot canvas with the staircase line plot.
Create a plot canvas with the staircase line plot.
a n x 2 or n x 3 matrix that describes coordinates of points.
3D surface plot.
3D surface plot.
the x-axis values of surface.
the y-axis values of surface.
the z-axis values of surface.
the color palette.
a tuple of window frame and plot canvas which can be added other shapes.
3D surface plot.
3D surface plot.
the x-axis values of surface.
the y-axis values of surface.
the z-axis values of surface.
a tuple of window frame and plot canvas which can be added other shapes.
3D surface plot.
3D surface plot.
the z-axis values of surface.
the color palette.
a tuple of window frame and plot canvas which can be added other shapes.
3D surface plot.
3D surface plot.
the z-axis values of surface.
a tuple of window frame and plot canvas which can be added other shapes.
Wire frame plot.
Wire frame plot. A wire frame model specifies each edge of the physical object where two mathematically continuous smooth surfaces meet, or by connecting an object's constituent vertices using straight lines or curves.
a n-by-2 or n-by-3 array which are coordinates of n vertices.
an m-by-2 array of which each row is the vertex indices of two end points of each edge.
Data visualization operators.