Training sample evaluation tools

Training samples are created to represent classes in a supervised classification. Different classes should be separated in the multidimensional attribute space. If any of them are overlapping, you might consider merging them into one class. To check the separability and distribution of your training samples, Training Sample Manager provides three evaluation tools: a Histograms window, a Scatterplots window, and a Statistics window. These tools are accessible as buttons on the manager.

The Histograms window

The Histograms window allows you to compare the distribution of multiple training samples. If the training samples represent different classes, their histograms should not overlap each other.

The following image shows an example of the Histograms window:

The Histograms evaluation window
The Histograms evaluation window

The Scatterplots window

The Scatterplots window is another way to compare multiple training samples. If the training samples represent different classes, their scatterplots should not overlap.

The following image shows an example of the Scatterplots evaluation window:

The Scatterplots evaluation window
The Scatterplots evaluation window

The Statistics window

The Statistics window displays the statistics for the selected classes.

The following image shows an example of the Statistics window:

The Statistics window
The Statistics window

Related Topics

12/16/2013