### Function Reference: `confusionchart`

statistics: confusionchart (trueLabels, predictedLabels)
statistics: confusionchart (m)
statistics: confusionchart (m, classLabels)
statistics: confusionchart (parent, …)
statistics: confusionchart (…, prop, val, …)
statistics: cm = confusionchart (…)

Display a chart of a confusion matrix.

The two vectors of values trueLabels and predictedLabels, which are used to compute the confusion matrix, must be defined with the same format as the inputs of `confusionmat`. Otherwise a confusion matrix m as computed by `confusionmat` can be given.

classLabels is an array of labels, i.e. the list of the class names.

If the first argument is a handle to a `figure` or to a `uipanel`, then the confusion matrix chart is displayed inside that object.

Optional property/value pairs are passed directly to the underlying objects, e.g. `"xlabel"`, `"ylabel"`, `"title"`, `"fontname"`, `"fontsize"` etc.

The optional return value cm is a `ConfusionMatrixChart` object. Specific properties of a `ConfusionMatrixChart` object are:

- `"DiagonalColor"` The color of the patches on the diagonal, default is [0.0, 0.4471, 0.7412].
- `"OffDiagonalColor"` The color of the patches off the diagonal, default is [0.851, 0.3255, 0.098].
- `"GridVisible"` Available values: `on` (default), `off`.
- `"Normalization"` Available values: `absolute` (default), `column-normalized`, `row-normalized`, `total-normalized`.
- `"ColumnSummary"` Available values: `off` (default), `absolute`, `column-normalized`,`total-normalized`.
- `"RowSummary"` Available values: `off` (default), `absolute`, `row-normalized`, `total-normalized`.

Run `demo confusionchart` to see some examples.

See also: confusionmat, sortClasses

Source Code: confusionchart

### Example: 1

     ## Setting the chart properties
     Yt = [8 5 6 8 5 3 1 6 4 2 5 3 1 4]';
     Yp = [8 5 6 8 5 2 3 4 4 5 5 7 2 6]';
     confusionchart (Yt, Yp, "Title", ...
       "Demonstration with summaries","Normalization",...
       "absolute","ColumnSummary", "column-normalized","RowSummary",...
       "row-normalized")

    ans =

    ConfusionMatrixChart with properties:

    	NormalizedValues: [ 8x8 double ]
    	ClassLabels: { 8x1 cell }

### Example: 2

     ## Cellstr as inputs
     Yt = {"Positive", "Positive", "Positive", "Negative", "Negative"};
     Yp = {"Positive", "Positive", "Negative", "Negative", "Negative"};
     m = confusionmat (Yt, Yp);
     confusionchart (m, {"Positive", "Negative"});

### Example: 3

     ## Editing the object properties
     Yt = {"Positive", "Positive", "Positive", "Negative", "Negative"};
     Yp = {"Positive", "Positive", "Negative", "Negative", "Negative"};
     cm = confusionchart (Yt, Yp);
     cm.Title = "This is an example with a green diagonal";
     cm.DiagonalColor = [0.4660, 0.6740, 0.1880];

### Example: 5

     ## Sorting classes
     Yt = [8 5 6 8 5 3 1 6 4 2 5 3 1 4]';
     Yp = [8 5 6 8 5 2 3 4 4 5 5 7 2 6]';
     cm = confusionchart (Yt, Yp, "Title", ...
       "Classes are sorted in ascending order");
     cm = confusionchart (Yt, Yp, "Title", ...
       "Classes are sorted according to clusters");
     sortClasses (cm, "cluster");