This tool calculates the Kappa index of agreement (KIA), or Cohen's Kappa, for two categorical input raster images (`input1` and `input2`). The KIA is a measure of inter-rater reliability (i.e. classification accuracy) and is widely applied in many fields, notably remote sensing. For example, The KIA is often used as a means of assessing the accuracy of an image classification analysis. The KIA can be interpreted as the percentage improvement that the underlying classification has over and above a random classifier (i.e. random assignment to categories). The user must specify the output HTML file (`output`). The input images must be of a categorical data type, i.e. contain classes. As a measure of classification accuracy, the KIA is more robust than the overall percent agreement because it takes into account the agreement occurring by chance. A KIA of 0 would indicate that the classifier is no better than random class assignment. In addition to the KIA, this tool will also output the producer's and user's accuracy, the overall accuracy, and the error matrix.

## See Also

cross_tabulation

## Function Signature

`def kappa_index(self, class_raster: Raster, reference_raster: Raster, output_html_file: str = "") -> None: ...`

## Project Links

WbW Homepage User Manual Support WbW