A character vector specifying the label for the x-axis. Default is "Predicted Class".

A character vector specifying the label for the y-axis. Default is "True Class".

A character vector specifying the title of the confusion matrix chart. Default is empty string.

A character vector specifying the font name used for all text elements in the chart. Default is empty string, which uses the axes font name.

A numeric scalar specifying the font size used for all text elements in the chart. Default is 0, which uses the axes font size.

A 1x3 RGB vector specifying the color for the diagonal elements of the confusion matrix, which represent correct classifications. Default is [0.0, 0.4471, 0.7412].

A 1x3 RGB vector specifying the color for the off-diagonal elements of the confusion matrix, which represent misclassifications. Default is [0.8510, 0.3255, 0.0980].

A character vector specifying how to normalize the confusion matrix values. Supported values are:

• 'absolute' - Display absolute counts (default)
• 'column-normalized' - Normalize by column totals
• 'row-normalized' - Normalize by row totals
• 'total-normalized' - Normalize by total number of observations

A character vector specifying whether and how to display column summaries. Supported values are:

• 'off' - Do not display column summary (default)
• 'absolute' - Display absolute counts
• 'column-normalized' - Display normalized by column
• 'total-normalized' - Display normalized by total

A character vector specifying whether and how to display row summaries. Supported values are:

• 'off' - Do not display row summary (default)
• 'absolute' - Display absolute counts
• 'row-normalized' - Display normalized by row
• 'total-normalized' - Display normalized by total

A character vector specifying whether to display grid lines in the confusion matrix. Supported values are:

• 'on' - Display grid lines (default)
• 'off' - Hide grid lines

A character vector specifying the visibility of the object’s handle. Supported values are 'on', 'off', and 'callback'.

A 1x4 numeric vector specifying the outer position of the chart in the format [left, bottom, width, height].

A 1x4 numeric vector specifying the position of the chart in the format [left, bottom, width, height].

A character vector specifying the units for the position properties. Supported values are 'centimeters', 'characters', 'inches', 'normalized', 'pixels', and 'points'.

A cell array of character vectors containing the class labels used in the confusion matrix. This property is read-only.

A numeric matrix containing the normalized confusion matrix values according to the current normalization setting. This property is read-only.

A handle to the parent figure or container object. This property is read-only.

statistics: cmc = ConfusionMatrixChart (hax, cm, cl)

statistics: cmc = ConfusionMatrixChart (…, name, value)

cmc = ConfusionMatrixChart (hax, cm, cl) returns a ConfusionMatrixChart object with parent axes hax, confusion matrix cm, and class labels cl.

• hax must be a valid axes handle where the chart will be displayed.
• cm must be a square numeric matrix containing the confusion matrix values, where rows represent true classes and columns represent predicted classes.
• cl must be a cell array of character vectors containing the class labels. The number of labels must match the size of the confusion matrix.

cmc = ConfusionMatrixChart (…, name, value) returns a ConfusionMatrixChart object with additional parameters specified by name, value paired arguments:

See also: confusionchart

ConfusionMatrixChart: disp (cmc)

disp (cmc) displays the main properties of the ConfusionMatrixChart object cmc, including the normalized values and class labels.

See also: ConfusionMatrixChart

ConfusionMatrixChart: sortClasses (cmc, order)

sortClasses (cmc, order) sorts the classes in the confusion matrix chart cmc according to the specified order.

order can be:

• A cell array of class labels in the desired order
• 'auto' - Sort class labels alphabetically
• 'ascending-diagonal' - Sort by ascending diagonal values
• 'descending-diagonal' - Sort by descending diagonal values
• 'cluster' - Sort using hierarchical clustering

When using 'cluster', the classes are grouped based on similarity using hierarchical clustering, which can help identify groups of frequently confused classes.

See also: confusionchart, linkage, pdist

 cm = ConfusionMatrixChart (gca, [1 2; 1 2], {'A','B'}, {'XLabel','LABEL A'})

cm =

ConfusionMatrixChart with properties:

	NormalizedValues: [ 2x2 double ]
	ClassLabels: { 1x2 cell }

 NormalizedValues = cm.NormalizedValues

NormalizedValues =

   1   2
   1   2

 ClassLabels = cm.ClassLabels

ClassLabels =
  1x2 cell array

    {'A'}    {'B'}