This paper has presented new algorithms for inducing alternating decision trees in the multiclass setting. Treating the multiclass problem as a number of binary classification problems and using the two-class ADTree method produces accurate
results from large numbers of trees. Although ADTrees can be merged, the size of the combined tree prohibits its use as a practical method, especially if interpretable models are a requirement.